From c2685646c9a2be4cdaf9d91f26a5ce7e9faf1680 Mon Sep 17 00:00:00 2001 From: ugur Date: Wed, 3 Apr 2024 09:43:04 +0100 Subject: [PATCH 01/18] Moved anndata to rdf process to a new folder --- .github/workflows/docker-publish.yml | 2 +- .gitignore | 1 + Dockerfile => anndata2rdf/Dockerfile | 0 docker-compose.yml => anndata2rdf/docker-compose.yml | 0 requirements.txt => anndata2rdf/requirements.txt | 0 {src => anndata2rdf/src}/csv_parser.py | 0 {src => anndata2rdf/src}/generate_rdf.py | 0 {src => anndata2rdf/src}/process.py | 0 {src => anndata2rdf/src}/pull_anndata.py | 0 9 files changed, 2 insertions(+), 1 deletion(-) rename Dockerfile => anndata2rdf/Dockerfile (100%) rename docker-compose.yml => anndata2rdf/docker-compose.yml (100%) rename requirements.txt => anndata2rdf/requirements.txt (100%) rename {src => anndata2rdf/src}/csv_parser.py (100%) rename {src => anndata2rdf/src}/generate_rdf.py (100%) rename {src => anndata2rdf/src}/process.py (100%) rename {src => anndata2rdf/src}/pull_anndata.py (100%) diff --git a/.github/workflows/docker-publish.yml b/.github/workflows/docker-publish.yml index 08c6e79..4875d16 100644 --- a/.github/workflows/docker-publish.yml +++ b/.github/workflows/docker-publish.yml @@ -54,7 +54,7 @@ jobs: - name: Build and push Docker image uses: docker/build-push-action@ad44023a93711e3deb337508980b4b5e9bcdc5dc with: - context: . + context: "{{defaultContext}}:anndata2rdf" push: true platforms: linux/amd64,linux/arm64 tags: ${{ steps.meta.outputs.tags }} diff --git a/.gitignore b/.gitignore index 68bc17f..6597a4f 100644 --- a/.gitignore +++ b/.gitignore @@ -1,5 +1,6 @@ # Byte-compiled / optimized / DLL files __pycache__/ +src/__pycache__/ *.py[cod] *$py.class diff --git a/Dockerfile b/anndata2rdf/Dockerfile similarity index 100% rename from Dockerfile rename to anndata2rdf/Dockerfile diff --git a/docker-compose.yml b/anndata2rdf/docker-compose.yml similarity index 100% rename from docker-compose.yml rename to anndata2rdf/docker-compose.yml diff --git a/requirements.txt b/anndata2rdf/requirements.txt similarity index 100% rename from requirements.txt rename to anndata2rdf/requirements.txt diff --git a/src/csv_parser.py b/anndata2rdf/src/csv_parser.py similarity index 100% rename from src/csv_parser.py rename to anndata2rdf/src/csv_parser.py diff --git a/src/generate_rdf.py b/anndata2rdf/src/generate_rdf.py similarity index 100% rename from src/generate_rdf.py rename to anndata2rdf/src/generate_rdf.py diff --git a/src/process.py b/anndata2rdf/src/process.py similarity index 100% rename from src/process.py rename to anndata2rdf/src/process.py diff --git a/src/pull_anndata.py b/anndata2rdf/src/pull_anndata.py similarity index 100% rename from src/pull_anndata.py rename to anndata2rdf/src/pull_anndata.py From a70496f332ebff45502ef312e612901d7df2b87c Mon Sep 17 00:00:00 2001 From: ugur Date: Thu, 4 Apr 2024 13:58:36 +0100 Subject: [PATCH 02/18] Updated docker-compose.yml --- anndata2rdf/docker-compose.yml | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/anndata2rdf/docker-compose.yml b/anndata2rdf/docker-compose.yml index 905bb4d..6dfbb69 100644 --- a/anndata2rdf/docker-compose.yml +++ b/anndata2rdf/docker-compose.yml @@ -2,10 +2,12 @@ version: '3.8' services: anndata2rdf: - image: anndata2rdf:latest + image: ghcr.io/obophenotype/cl_kb:main@sha256:26384c8de0416e3d9888407d73472d12709d0924cd509081f74b9b5e17e634cf container_name: anndata_to_rdf volumes: - ./src/config:/app/src/config - ./src/curated_data:/app/src/curated_data - ./src/dataset:/app/src/dataset - - ./src/graph:/app/src/graph + - obask_data:/app/src/graph +volumes: + obask_data: From b4456ce7311f55393c84dd54bf0de81e7488a95a Mon Sep 17 00:00:00 2001 From: ugur Date: Thu, 4 Apr 2024 13:58:49 +0100 Subject: [PATCH 03/18] Added README.md files --- anndata2rdf/src/config/README.md | 3 +++ anndata2rdf/src/curated_data/README.md | 2 ++ anndata2rdf/src/dataset/README.md | 2 ++ anndata2rdf/src/graph/README.md | 2 ++ 4 files changed, 9 insertions(+) create mode 100644 anndata2rdf/src/config/README.md create mode 100644 anndata2rdf/src/curated_data/README.md create mode 100644 anndata2rdf/src/dataset/README.md create mode 100644 anndata2rdf/src/graph/README.md diff --git a/anndata2rdf/src/config/README.md b/anndata2rdf/src/config/README.md new file mode 100644 index 0000000..236cdee --- /dev/null +++ b/anndata2rdf/src/config/README.md @@ -0,0 +1,3 @@ +### `config` +Contains YAML files generated from the CSV files in the `curated_data` directory. These configurations are used to +guide the download process of datasets from CxG. \ No newline at end of file diff --git a/anndata2rdf/src/curated_data/README.md b/anndata2rdf/src/curated_data/README.md new file mode 100644 index 0000000..05eea73 --- /dev/null +++ b/anndata2rdf/src/curated_data/README.md @@ -0,0 +1,2 @@ +### `curated_data` +This directory holds the original CSV files that are used as the starting point of the data processing pipeline. These files are read and processed to generate corresponding YAML configurations. \ No newline at end of file diff --git a/anndata2rdf/src/dataset/README.md b/anndata2rdf/src/dataset/README.md new file mode 100644 index 0000000..7a2aaf7 --- /dev/null +++ b/anndata2rdf/src/dataset/README.md @@ -0,0 +1,2 @@ +### `dataset` +Stores the datasets downloaded according to the instructions specified in the YAML files located in the `config` directory. These datasets are then used for further processing and analysis. \ No newline at end of file diff --git a/anndata2rdf/src/graph/README.md b/anndata2rdf/src/graph/README.md new file mode 100644 index 0000000..0b5d20a --- /dev/null +++ b/anndata2rdf/src/graph/README.md @@ -0,0 +1,2 @@ +### `graph` +Contains the OWL (Web Ontology Language) files that are generated from the datasets in the `dataset` directory. These files represent the structured data in a format that is suitable for semantic web applications. \ No newline at end of file From 3962b8e0653beeb145c8f374df76275794b7b64a Mon Sep 17 00:00:00 2001 From: ugur Date: Thu, 4 Apr 2024 14:03:11 +0100 Subject: [PATCH 04/18] Added obask pipeline --- .github/workflows/schema_validator.yaml | 50 ++++++++ cl_kb_pipeline/README.md | 5 + cl_kb_pipeline/config/collectdata/config.env | 2 + .../sparql/delete_blocked_entities.ru | 18 +++ .../sparql/delete_blocked_relations.ru | 30 +++++ .../sparql/delete_embargoed_channels.ru | 31 +++++ .../sparql/delete_embargoed_datasets.ru | 28 ++++ .../sparql/delete_embargoed_images.ru | 35 +++++ .../sparql/embargoed_datasets_dev.sparql | 25 ++++ .../sparql/embargoed_datasets_prod.sparql | 19 +++ .../sparql/select_blocked_entities.sparql | 15 +++ .../sparql/select_blocked_relations.sparql | 22 ++++ .../select_embargoed_channels_dev.sparql | 29 +++++ .../select_embargoed_channels_prod.sparql | 25 ++++ .../select_embargoed_datasets_dev.sparql | 26 ++++ .../select_embargoed_datasets_prod.sparql | 22 ++++ .../sparql/select_embargoed_images_dev.sparql | 28 ++++ .../select_embargoed_images_prod.sparql | 24 ++++ .../sparql/select_hasDbXref_relations.sparql | 13 ++ .../config/collectdata/sparql/terms.sparql | 7 + .../config/collectdata/vfb_fullontologies.txt | 1 + .../config/collectdata/vfb_slices.txt | 1 + cl_kb_pipeline/config/dumps/README.md | 28 ++++ cl_kb_pipeline/config/dumps/config.env | 4 + .../config/dumps/neo4j2owl-config.yaml | 53 ++++++++ .../config/dumps/sparql/_dump_all.sparql | 6 + .../config/dumps/sparql/construct_all.sparql | 6 + .../sparql/construct_deprecation_label.sparql | 7 + .../dumps/sparql/construct_exemplar_of.sparql | 18 +++ .../dumps/sparql/construct_has_image.sparql | 14 ++ .../construct_has_neuron_connectivity.sparql | 9 ++ .../construct_has_region_connectivity.sparql | 10 ++ .../dumps/sparql/construct_image_names.sparql | 20 +++ .../dumps/sparql/construct_non_literal.sparql | 11 ++ .../sparql/construct_ontology_metadata.sparql | 21 +++ .../sparql/construct_preferred_roots.sparql | 7 + .../construct_subclass_of_intersection.sparql | 16 +++ .../config/dumps/sparql/construct_test.sparql | 23 ++++ .../dumps/sparql/construct_test2.sparql | 16 +++ cl_kb_pipeline/config/update-prod/config.env | 3 + .../config/update-prod/pdb_set_indices.neo4j | 11 ++ .../config/updatetriplestore/config.env | 3 + .../config/updatetriplestore/rdf4j.txt | 17 +++ cl_kb_pipeline/docker-compose.yml | 121 ++++++++++++++++++ cl_kb_pipeline/src/__init__.py | 0 cl_kb_pipeline/src/test_neo2owl_config.py | 5 + cl_kb_pipeline/src/utils/__init__.py | 0 cl_kb_pipeline/src/utils/schema_test_tools.py | 118 +++++++++++++++++ 48 files changed, 1003 insertions(+) create mode 100644 .github/workflows/schema_validator.yaml create mode 100644 cl_kb_pipeline/README.md create mode 100644 cl_kb_pipeline/config/collectdata/config.env create mode 100644 cl_kb_pipeline/config/collectdata/sparql/delete_blocked_entities.ru create mode 100644 cl_kb_pipeline/config/collectdata/sparql/delete_blocked_relations.ru create mode 100644 cl_kb_pipeline/config/collectdata/sparql/delete_embargoed_channels.ru create mode 100644 cl_kb_pipeline/config/collectdata/sparql/delete_embargoed_datasets.ru create mode 100644 cl_kb_pipeline/config/collectdata/sparql/delete_embargoed_images.ru create mode 100644 cl_kb_pipeline/config/collectdata/sparql/embargoed_datasets_dev.sparql create mode 100644 cl_kb_pipeline/config/collectdata/sparql/embargoed_datasets_prod.sparql create mode 100644 cl_kb_pipeline/config/collectdata/sparql/select_blocked_entities.sparql create mode 100644 cl_kb_pipeline/config/collectdata/sparql/select_blocked_relations.sparql create mode 100644 cl_kb_pipeline/config/collectdata/sparql/select_embargoed_channels_dev.sparql create mode 100644 cl_kb_pipeline/config/collectdata/sparql/select_embargoed_channels_prod.sparql create mode 100644 cl_kb_pipeline/config/collectdata/sparql/select_embargoed_datasets_dev.sparql create mode 100644 cl_kb_pipeline/config/collectdata/sparql/select_embargoed_datasets_prod.sparql create mode 100644 cl_kb_pipeline/config/collectdata/sparql/select_embargoed_images_dev.sparql create mode 100644 cl_kb_pipeline/config/collectdata/sparql/select_embargoed_images_prod.sparql create mode 100644 cl_kb_pipeline/config/collectdata/sparql/select_hasDbXref_relations.sparql create mode 100644 cl_kb_pipeline/config/collectdata/sparql/terms.sparql create mode 100644 cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt create mode 100644 cl_kb_pipeline/config/collectdata/vfb_slices.txt create mode 100644 cl_kb_pipeline/config/dumps/README.md create mode 100644 cl_kb_pipeline/config/dumps/config.env create mode 100644 cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml create mode 100644 cl_kb_pipeline/config/dumps/sparql/_dump_all.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_all.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_deprecation_label.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_exemplar_of.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_has_image.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_has_neuron_connectivity.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_has_region_connectivity.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_image_names.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_non_literal.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_ontology_metadata.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_preferred_roots.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_subclass_of_intersection.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_test.sparql create mode 100644 cl_kb_pipeline/config/dumps/sparql/construct_test2.sparql create mode 100644 cl_kb_pipeline/config/update-prod/config.env create mode 100644 cl_kb_pipeline/config/update-prod/pdb_set_indices.neo4j create mode 100644 cl_kb_pipeline/config/updatetriplestore/config.env create mode 100644 cl_kb_pipeline/config/updatetriplestore/rdf4j.txt create mode 100644 cl_kb_pipeline/docker-compose.yml create mode 100644 cl_kb_pipeline/src/__init__.py create mode 100644 cl_kb_pipeline/src/test_neo2owl_config.py create mode 100644 cl_kb_pipeline/src/utils/__init__.py create mode 100644 cl_kb_pipeline/src/utils/schema_test_tools.py diff --git a/.github/workflows/schema_validator.yaml b/.github/workflows/schema_validator.yaml new file mode 100644 index 0000000..3dfa3eb --- /dev/null +++ b/.github/workflows/schema_validator.yaml @@ -0,0 +1,50 @@ +name: YAML schema validator +on: + # Triggers the workflow on pull request events but only for the main branch + pull_request: + branches: [ main ] + paths: + - 'cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml' + +jobs: + yaml-schema-validation: + runs-on: macos-latest + steps: + - uses: actions/checkout@v2 + - name: Set up Python 3.8 + uses: actions/setup-python@v3 + with: + python-version: 3.8 + - name: Install dependencies + run: pip install -r "ruamel.yaml==0.17.21" "jsonschema==4.4.0" + - name: Schema validation + id: schema + run: | + python src/test_neo2owl_config.py + - name: Prepare schema validator comment + if: failure() + run: | + echo "cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml file failed the schema validation check " > comment.md; cat validation.report >> comment.md +# - name: install Yamale +# run: brew install yamale +# - name: Regex based DL validation +# id: validation +# run: | +# yamale -s schema.yaml config/dumps/neo4j2owl-config.yaml | tee output +# tail -n +4 output > validation.report +# echo ::set-output name=report::$(cat output) +# - name: Prepare DL validator comment +# if: contains(steps.validation.outputs.report, 'Error') +# run: | +# echo "
config/prod/neo4j2owl-config.yaml file failed the regex based DL validation check " > comment.md; cat validation.report >> comment.md +# exit 1 + - name: Prepare success comment + run: | + echo "cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml file passed validation check " > comment.md + - name: Post comment validator comment + if: always() + env: + GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}} + uses: NejcZdovc/comment-pr@v1.1.1 + with: + file: "../../comment.md" diff --git a/cl_kb_pipeline/README.md b/cl_kb_pipeline/README.md new file mode 100644 index 0000000..ae8f4f5 --- /dev/null +++ b/cl_kb_pipeline/README.md @@ -0,0 +1,5 @@ +# cl_kb_pipeline + +[OBASK pipeline](https://github.com/OBASKTools/obask) for cl_kb_pipeline. + +To run the pipeline, please follow the `Run your project` steps of the [OBASK quick start guide](https://obasktools.github.io/obask/quick_start/) \ No newline at end of file diff --git a/cl_kb_pipeline/config/collectdata/config.env b/cl_kb_pipeline/config/collectdata/config.env new file mode 100644 index 0000000..ca67c2b --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/config.env @@ -0,0 +1,2 @@ +EXPORT_KB_TO_OWL=false +COLLECT_BIBLIO_DATA=false diff --git a/cl_kb_pipeline/config/collectdata/sparql/delete_blocked_entities.ru b/cl_kb_pipeline/config/collectdata/sparql/delete_blocked_entities.ru new file mode 100644 index 0000000..e89830c --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/delete_blocked_entities.ru @@ -0,0 +1,18 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +DELETE { + ?s ?blocked . + ?s ?p ?o . +} +WHERE { + ?s ?blocked . + ?s ?p ?o . + FILTER(?blocked=true) . + FILTER(isIRI(?s)) +} + +### EDIT: this was obsoleted in the end in favour of a cypher solution, see process.sh. diff --git a/cl_kb_pipeline/config/collectdata/sparql/delete_blocked_relations.ru b/cl_kb_pipeline/config/collectdata/sparql/delete_blocked_relations.ru new file mode 100644 index 0000000..a847e52 --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/delete_blocked_relations.ru @@ -0,0 +1,30 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: +PREFIX rdf: + + +DELETE { + ?s ?p ?o . + ?r rdf:type owl:Axiom ; + owl:annotatedSource ?s ; + owl:annotatedProperty ?p ; + owl:annotatedTarget ?o ; + ?blocked; + ?bp ?bo; + +} WHERE { + ?s ?p ?o . + ?r rdf:type owl:Axiom ; + owl:annotatedSource ?s ; + owl:annotatedProperty ?p ; + owl:annotatedTarget ?o ; + ?blocked; + ?bp ?bo; + + FILTER(?blocked=true) . +} + +### EDIT: this was obsoleted in the end in favour of a cypher solution, see process.sh. diff --git a/cl_kb_pipeline/config/collectdata/sparql/delete_embargoed_channels.ru b/cl_kb_pipeline/config/collectdata/sparql/delete_embargoed_channels.ru new file mode 100644 index 0000000..2af89a0 --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/delete_embargoed_channels.ru @@ -0,0 +1,31 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +#Delete all ds:DataSet where ds.production is False +#Delete all i:Individual where (ds)-[:has_source]-(i:Individual)<-[:depicts]-(ch:Individual) WHERE ds.production is False + +DELETE { + ?channel ?channelrel ?channelval . +} + +WHERE { + + ?dataset n2o:nodeLabel ?nodelabel . # This selects all datasets + + OPTIONAL { + ?dataset n2oc:production ?production . + # n2oc:production is a bit brittle because IRI might be changed (risk!) + } + + ?image dct:source ?dataset . + ?channel ?image . # There does not always seem to be a channel + ?channel ?channelrel ?channelval . + + FILTER(?production=false || !bound(?production)) . + FILTER(?nodelabel="DataSet") +} + +### EDIT: this was obsoleted in the end in favour of a ROBOT solution, see process.sh. Using SPARQL this way is too memory consuming. diff --git a/cl_kb_pipeline/config/collectdata/sparql/delete_embargoed_datasets.ru b/cl_kb_pipeline/config/collectdata/sparql/delete_embargoed_datasets.ru new file mode 100644 index 0000000..c830daf --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/delete_embargoed_datasets.ru @@ -0,0 +1,28 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +#Delete all ds:DataSet where ds.production is False +#Delete all i:Individual where (ds)-[:has_source]-(i:Individual)<-[:depicts]-(ch:Individual) WHERE ds.production is False + +DELETE { + ?dataset ?dsrel ?dsval . +} + +WHERE { + + ?dataset n2o:nodeLabel ?nodelabel . # This selects all datasets + OPTIONAL { + ?dataset n2oc:production ?production . + # n2oc:production is a bit brittle because IRI might be changed (risk!) + } + + ?dataset ?dsrel ?dsval . + + FILTER(?production=false || !bound(?production)) . + FILTER(?nodelabel="DataSet") +} + +### EDIT: this was obsoleted in the end in favour of a ROBOT solution, see process.sh. Using SPARQL this way is too memory consuming. diff --git a/cl_kb_pipeline/config/collectdata/sparql/delete_embargoed_images.ru b/cl_kb_pipeline/config/collectdata/sparql/delete_embargoed_images.ru new file mode 100644 index 0000000..89b00bc --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/delete_embargoed_images.ru @@ -0,0 +1,35 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +#Delete all ds:DataSet where ds.production is False +#Delete all i:Individual where (ds)-[:has_source]-(i:Individual)<-[:depicts]-(ch:Individual) WHERE ds.production is False + +DELETE { + ?image ?imgrel ?imgval . + ?imgval ?p1 ?o1 . +} + +WHERE { + + ?dataset n2o:nodeLabel ?nodelabel . # This selects all datasets + + OPTIONAL { + ?dataset n2oc:production ?production . + # n2oc:production is a bit brittle because IRI might be changed (risk!) + } + + ?image dct:source ?dataset . #in case a dataset does not have images yet this is an optional clause + ?image ?imgrel ?imgval . + OPTIONAL { + ?imgval ?p1 ?o1 . + FILTER (isBlank(?imgval)) + } + + FILTER(?production=false || !bound(?production)) . + FILTER(?nodelabel="DataSet") +} + +### EDIT: this was obsoleted in the end in favour of a ROBOT solution, see process.sh. Using SPARQL this way is too memory consuming. diff --git a/cl_kb_pipeline/config/collectdata/sparql/embargoed_datasets_dev.sparql b/cl_kb_pipeline/config/collectdata/sparql/embargoed_datasets_dev.sparql new file mode 100644 index 0000000..9bda63f --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/embargoed_datasets_dev.sparql @@ -0,0 +1,25 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +SELECT DISTINCT ?dataset + +WHERE { + + ?dataset n2o:nodeLabel ?nodelabel . # This selects all datasets + OPTIONAL { + ?dataset n2oc:production ?production . + # n2oc:production is a bit brittle because IRI might be changed (risk!) + } + + OPTIONAL { + ?dataset n2oc:staging ?staged . + } + + IF((staging=false || unbound(staging)) && (prod = false || unbound(prod)) ) -----> EMBARGO + + FILTER( (?production=false || !bound(?production)) && (?staged=false || !bound(?staged)) ) . + FILTER(?nodelabel="DataSet") +} diff --git a/cl_kb_pipeline/config/collectdata/sparql/embargoed_datasets_prod.sparql b/cl_kb_pipeline/config/collectdata/sparql/embargoed_datasets_prod.sparql new file mode 100644 index 0000000..7f2ed94 --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/embargoed_datasets_prod.sparql @@ -0,0 +1,19 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +SELECT DISTINCT ?dataset + +WHERE { + + ?dataset n2o:nodeLabel ?nodelabel . # This selects all datasets + OPTIONAL { + ?dataset n2oc:production ?production . + # n2oc:production is a bit brittle because IRI might be changed (risk!) + } + + FILTER(?production=false || !bound(?production)) . + FILTER(?nodelabel="DataSet") +} diff --git a/cl_kb_pipeline/config/collectdata/sparql/select_blocked_entities.sparql b/cl_kb_pipeline/config/collectdata/sparql/select_blocked_entities.sparql new file mode 100644 index 0000000..841bda4 --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/select_blocked_entities.sparql @@ -0,0 +1,15 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +SELECT ?s ?p ?o . +WHERE { + ?s ?blocked . + ?s ?p ?o . + FILTER(?blocked=true) . + FILTER(isIRI(?s)) +} + +### EDIT: this was obsoleted in the end in favour of a cypher solution, see process.sh. diff --git a/cl_kb_pipeline/config/collectdata/sparql/select_blocked_relations.sparql b/cl_kb_pipeline/config/collectdata/sparql/select_blocked_relations.sparql new file mode 100644 index 0000000..697392a --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/select_blocked_relations.sparql @@ -0,0 +1,22 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: +PREFIX rdf: + + +SELECT ?s ?p ?o +WHERE { + ?s ?p ?o . + ?r rdf:type owl:Axiom ; + owl:annotatedSource ?s ; + owl:annotatedProperty ?p ; + owl:annotatedTarget ?o ; + ?blocked; + ?bp ?bo; + + FILTER(?blocked=true) . +} + +### EDIT: this was obsoleted in the end in favour of a cypher solution, see process.sh. diff --git a/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_channels_dev.sparql b/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_channels_dev.sparql new file mode 100644 index 0000000..1f96fbd --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_channels_dev.sparql @@ -0,0 +1,29 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +#Delete all ds:DataSet where ds.production is False +#Delete all i:Individual where (ds)-[:has_source]-(i:Individual)<-[:depicts]-(ch:Individual) WHERE ds.production is False + +SELECT DISTINCT ?channel +WHERE { + + ?dataset n2o:nodeLabel ?nodelabel . # This selects all datasets + + OPTIONAL { + ?dataset n2oc:production ?production . + # n2oc:production is a bit brittle because IRI might be changed (risk!) + } + + OPTIONAL { + ?dataset n2oc:staging ?staged . + } + + ?image dct:source ?dataset . + ?channel ?image . # There does not always seem to be a channel + + FILTER( (?production=false || !bound(?production)) && (?staged=false || !bound(?staged)) ) . + FILTER(?nodelabel="DataSet") +} diff --git a/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_channels_prod.sparql b/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_channels_prod.sparql new file mode 100644 index 0000000..90b57e4 --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_channels_prod.sparql @@ -0,0 +1,25 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +#Delete all ds:DataSet where ds.production is False +#Delete all i:Individual where (ds)-[:has_source]-(i:Individual)<-[:depicts]-(ch:Individual) WHERE ds.production is False + +SELECT DISTINCT ?channel +WHERE { + + ?dataset n2o:nodeLabel ?nodelabel . # This selects all datasets + + OPTIONAL { + ?dataset n2oc:production ?production . + # n2oc:production is a bit brittle because IRI might be changed (risk!) + } + + ?image dct:source ?dataset . + ?channel ?image . # There does not always seem to be a channel + + FILTER(?production=false || !bound(?production)) . + FILTER(?nodelabel="DataSet") +} diff --git a/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_datasets_dev.sparql b/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_datasets_dev.sparql new file mode 100644 index 0000000..15d268d --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_datasets_dev.sparql @@ -0,0 +1,26 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +#Delete all ds:DataSet where ds.production is False +#Delete all i:Individual where (ds)-[:has_source]-(i:Individual)<-[:depicts]-(ch:Individual) WHERE ds.production is False + +SELECT DISTINCT ?dataset +WHERE { + + ?dataset n2o:nodeLabel ?nodelabel . # This selects all datasets + + OPTIONAL { + ?dataset n2oc:production ?production . + # n2oc:production is a bit brittle because IRI might be changed (risk!) + } + + OPTIONAL { + ?dataset n2oc:staging ?staged . + } + + FILTER( (?production=false || !bound(?production)) && (?staged=false || !bound(?staged)) ) . + FILTER(?nodelabel="DataSet") +} diff --git a/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_datasets_prod.sparql b/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_datasets_prod.sparql new file mode 100644 index 0000000..2917a6f --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_datasets_prod.sparql @@ -0,0 +1,22 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +#Delete all ds:DataSet where ds.production is False +#Delete all i:Individual where (ds)-[:has_source]-(i:Individual)<-[:depicts]-(ch:Individual) WHERE ds.production is False + +SELECT DISTINCT ?dataset +WHERE { + + ?dataset n2o:nodeLabel ?nodelabel . # This selects all datasets + + OPTIONAL { + ?dataset n2oc:production ?production . + # n2oc:production is a bit brittle because IRI might be changed (risk!) + } + + FILTER(?production=false || !bound(?production)) . + FILTER(?nodelabel="DataSet") +} diff --git a/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_images_dev.sparql b/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_images_dev.sparql new file mode 100644 index 0000000..6b8e08f --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_images_dev.sparql @@ -0,0 +1,28 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +#Delete all ds:DataSet where ds.production is False +#Delete all i:Individual where (ds)-[:has_source]-(i:Individual)<-[:depicts]-(ch:Individual) WHERE ds.production is False + +SELECT DISTINCT ?image +WHERE { + + ?dataset n2o:nodeLabel ?nodelabel . # This selects all datasets + + OPTIONAL { + ?dataset n2oc:production ?production . + # n2oc:production is a bit brittle because IRI might be changed (risk!) + } + + OPTIONAL { + ?dataset n2oc:staging ?staged . + } + + ?image dct:source ?dataset . + + FILTER( (?production=false || !bound(?production)) && (?staged=false || !bound(?staged)) ) . + FILTER(?nodelabel="DataSet") +} diff --git a/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_images_prod.sparql b/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_images_prod.sparql new file mode 100644 index 0000000..ec44e6b --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/select_embargoed_images_prod.sparql @@ -0,0 +1,24 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +#Delete all ds:DataSet where ds.production is False +#Delete all i:Individual where (ds)-[:has_source]-(i:Individual)<-[:depicts]-(ch:Individual) WHERE ds.production is False + +SELECT DISTINCT ?image +WHERE { + + ?dataset n2o:nodeLabel ?nodelabel . # This selects all datasets + + OPTIONAL { + ?dataset n2oc:production ?production . + # n2oc:production is a bit brittle because IRI might be changed (risk!) + } + + ?image dct:source ?dataset . + + FILTER(?production=false || !bound(?production)) . + FILTER(?nodelabel="DataSet") +} diff --git a/cl_kb_pipeline/config/collectdata/sparql/select_hasDbXref_relations.sparql b/cl_kb_pipeline/config/collectdata/sparql/select_hasDbXref_relations.sparql new file mode 100644 index 0000000..5d481b6 --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/select_hasDbXref_relations.sparql @@ -0,0 +1,13 @@ +PREFIX owl: +PREFIX rdfs: +PREFIX obo: +PREFIX oboInOwl: + +SELECT DISTINCT ?id ?axiom ?descXref +WHERE { + ?id obo:IAO_0000115 ?description. + ?axiom owl:annotatedSource ?id. + ?axiom owl:annotatedProperty obo:IAO_0000115. + ?axiom oboInOwl:hasDbXref ?descXref. +} +ORDER BY ASC(?id) diff --git a/cl_kb_pipeline/config/collectdata/sparql/terms.sparql b/cl_kb_pipeline/config/collectdata/sparql/terms.sparql new file mode 100644 index 0000000..0f8b90c --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/sparql/terms.sparql @@ -0,0 +1,7 @@ +SELECT DISTINCT ?term +WHERE { + { ?s1 ?p1 ?term . } + UNION + { ?term ?p2 ?o2 . } + FILTER(isIRI(?term)) +} diff --git a/cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt b/cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt new file mode 100644 index 0000000..5d68940 --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt @@ -0,0 +1 @@ +http://purl.obolibrary.org/obo/cl/cl-base.owl \ No newline at end of file diff --git a/cl_kb_pipeline/config/collectdata/vfb_slices.txt b/cl_kb_pipeline/config/collectdata/vfb_slices.txt new file mode 100644 index 0000000..03ae6a8 --- /dev/null +++ b/cl_kb_pipeline/config/collectdata/vfb_slices.txt @@ -0,0 +1 @@ +http://purl.obolibrary.org/obo/ro.owl diff --git a/cl_kb_pipeline/config/dumps/README.md b/cl_kb_pipeline/config/dumps/README.md new file mode 100644 index 0000000..cadea6b --- /dev/null +++ b/cl_kb_pipeline/config/dumps/README.md @@ -0,0 +1,28 @@ +### Adding semantic tags via SPARQL queries + + +1. Create new sparql construct statement in sparql/, naming it 'construct_{name}.sparql', where {name} indicates the semantic tag to add e.g. sparql/construct_Metazoan.sparql. The sparql construct should add the semantic tag via the annotation property http://n2o.neo/property/nodeLabel +2. Add the label name to the to the correct DUMPS variable for the service is should appear in (DUMPS_SOLR, DUMPS_PDB, DUMPS_OWLERY) in dumps/config.env + +e.g. + +construct_has_image.sparql file has content + +```sparql +PREFIX owl: +PREFIX rdf: +PREFIX foaf: + +CONSTRUCT { + ?x "has_image" . +} +WHERE { + # Some SELECT criteria in here. +} +``` + +dumps/config.env has + +DUMPS_SOLR="all deprecation has_image" + +=> `has_image` and `deprecation` (obsolete) semantics tags loaded along with complete dump of triplestore content (all) to SOLR diff --git a/cl_kb_pipeline/config/dumps/config.env b/cl_kb_pipeline/config/dumps/config.env new file mode 100644 index 0000000..fe1f542 --- /dev/null +++ b/cl_kb_pipeline/config/dumps/config.env @@ -0,0 +1,4 @@ +SPARQL_ENDPOINT=http://triplestore:8080/rdf4j-server/repositories/obask +DUMPS_SOLR="all" +DUMPS_PDB="all" +DUMPS_OWLERY="all" diff --git a/cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml b/cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml new file mode 100644 index 0000000..43adebe --- /dev/null +++ b/cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml @@ -0,0 +1,53 @@ +allow_entities_without_labels: true +index: false +testmode: false +batch: true +safe_label: loose +batch_size: 100000000 +relation_type_threshold: 0.95 +represent_values_and_annotations_as_json: + iris: + - "http://purl.obolibrary.org/obo/IAO_0000115" + - "http://www.geneontology.org/formats/oboInOwl#hasExactSynonym" + - "http://www.geneontology.org/formats/oboInOwl#hasNarrowSynonym" + - "http://www.geneontology.org/formats/oboInOwl#hasBroadSynonym" + - "http://www.geneontology.org/formats/oboInOwl#hasRelatedSynonym" + +neo_node_labelling: + - classes: + - CL:0000000 + label: Cell + +curie_map: + GITHUB: https://github.com/ + GITHUBH: http://github.com/ + PMID: http://www.ncbi.nlm.nih.gov/pubmed/ + orcid: https://orcid.org/ + doi: https://doi.org/ + rdfs: http://www.w3.org/2000/01/rdf-schema# + ncbigene: http://www.ncbi.nlm.nih.gov/gene/ + cc: http://creativecommons.org/ns# + pato_rel: http://purl.obolibrary.org/obo/pato# + so_rel: http://purl.obolibrary.org/obo/so# + ro_rel: http://www.obofoundry.org/ro/ro.owl# + owl: http://www.w3.org/2002/07/owl# + skos: http://www.w3.org/2004/02/skos/core# + ensembl: http://identifiers.org/ensembl/ + RO: http://purl.obolibrary.org/obo/RO_ + UBERON: http://purl.obolibrary.org/obo/UBERON_ + CL: http://purl.obolibrary.org/obo/CL_ + n2o: http://n2o.neo/custom/ + ILX: http://uri.interlex.org/base/ilx_ + NCBITaxon: http://purl.obolibrary.org/obo/NCBITaxon_ + PR: http://purl.obolibrary.org/obo/PR_ + SO: http://purl.obolibrary.org/obo/SO_ + OBI: http://purl.obolibrary.org/obo/OBI_ + PCL: http://purl.obolibrary.org/obo/PCL_ + +filters: + solr: + exclusion: + iri_prefix: + - http://virtualflybrain.org/reports/VFBc_ + neo4j_node_label: + - Channel diff --git a/cl_kb_pipeline/config/dumps/sparql/_dump_all.sparql b/cl_kb_pipeline/config/dumps/sparql/_dump_all.sparql new file mode 100644 index 0000000..b92b0bc --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/_dump_all.sparql @@ -0,0 +1,6 @@ +PREFIX : + +CONSTRUCT { ?x ?p ?y . } + +WHERE {?x ?p ?y .} + diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_all.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_all.sparql new file mode 100644 index 0000000..b92b0bc --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_all.sparql @@ -0,0 +1,6 @@ +PREFIX : + +CONSTRUCT { ?x ?p ?y . } + +WHERE {?x ?p ?y .} + diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_deprecation_label.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_deprecation_label.sparql new file mode 100644 index 0000000..2fff814 --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_deprecation_label.sparql @@ -0,0 +1,7 @@ +CONSTRUCT { + ?x "Deprecated" . +} +WHERE { + ?x true . + FILTER(isIRI(?x)) +} diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_exemplar_of.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_exemplar_of.sparql new file mode 100644 index 0000000..e77295c --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_exemplar_of.sparql @@ -0,0 +1,18 @@ +PREFIX rdfs: +PREFIX obo: +PREFIX owl: +PREFIX rdf: +PREFIX skos: + +CONSTRUCT { + ?indv obo:RO_0015002 ?class . +} +WHERE { + ?class rdfs:subClassOf* obo:CL_0000127. + ?class owl:equivalentClass ?eq. + ?eq owl:intersectionOf ?intersect. + ?intersect rdf:rest ?rest. + ?rest rdf:first ?first. + ?first owl:onProperty obo:RO_0015001. + ?first owl:hasValue ?indv. +} diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_has_image.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_has_image.sparql new file mode 100644 index 0000000..5352c28 --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_has_image.sparql @@ -0,0 +1,14 @@ +PREFIX owl: +PREFIX rdf: +PREFIX foaf: + +CONSTRUCT { + ?x "has_image" . +} +WHERE { + ?y foaf:depicts ?x . + ?y ?z . + ?x rdf:type owl:NamedIndividual . + ?y rdf:type owl:NamedIndividual . + ?z rdf:type owl:NamedIndividual . +} diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_has_neuron_connectivity.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_has_neuron_connectivity.sparql new file mode 100644 index 0000000..b41c48b --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_has_neuron_connectivity.sparql @@ -0,0 +1,9 @@ +PREFIX owl: +PREFIX rdf: + +CONSTRUCT { + ?x "has_neuron_connectivity" . +} +WHERE { + ?x | ?y . +} diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_has_region_connectivity.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_has_region_connectivity.sparql new file mode 100644 index 0000000..488f2dd --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_has_region_connectivity.sparql @@ -0,0 +1,10 @@ +PREFIX owl: +PREFIX rdf: + +CONSTRUCT { + ?x "has_region_connectivity" . +} +WHERE { + ?x | ?y . + ?x rdf:type owl:NamedIndividual . +} diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_image_names.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_image_names.sparql new file mode 100644 index 0000000..0a48992 --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_image_names.sparql @@ -0,0 +1,20 @@ +PREFIX rdfs: +PREFIX owl: +PREFIX n2o: +PREFIX n2oc: +PREFIX dct: + +CONSTRUCT { +?anatomical_indiv ?filename . +?anatomical_indiv ?thumbnail . +} +WHERE { + ?channel ?anatomical_indiv . + ?anno owl:annotatedSource ?channel . + ?anno owl:annotatedProperty . + ?anno n2oc:folder ?folder . + OPTIONAL { + ?anno n2oc:filename ?filename . + } + BIND(CONCAT(STR( ?folder ),"thumbnail.png") AS ?thumbnail ) . +} \ No newline at end of file diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_non_literal.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_non_literal.sparql new file mode 100644 index 0000000..248917e --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_non_literal.sparql @@ -0,0 +1,11 @@ +PREFIX : +PREFIX rdfs: + +CONSTRUCT { ?x ?p ?y . } + +WHERE { + ?x ?p ?y . + FILTER(!isLiteral(?y)) +} + +# LIMIT 5000 \ No newline at end of file diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_ontology_metadata.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_ontology_metadata.sparql new file mode 100644 index 0000000..edf5f4b --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_ontology_metadata.sparql @@ -0,0 +1,21 @@ +PREFIX : +PREFIX rdfs: +PREFIX obo: +PREFIX owl: +PREFIX rdf: +PREFIX skos: +PREFIX dc: + +CONSTRUCT { + :Ontology rdf:type owl:Class . + :Ontology rdfs:label ?title . + :Ontology dc:title ?title . +# :Ontology dc:description ?desc . + :Ontology owl:versionInfo ?versionInfo . +} +WHERE { + ?ontology rdf:type owl:Ontology . + ?ontology dc:title ?title . +# ?ontology dc:description ?desc . + ?ontology owl:versionInfo ?versionInfo . +} diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_preferred_roots.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_preferred_roots.sparql new file mode 100644 index 0000000..68b58cd --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_preferred_roots.sparql @@ -0,0 +1,7 @@ +CONSTRUCT { + # ?y true . + ?y "preferred_root" . +} +WHERE { + ?x ?y . +} \ No newline at end of file diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_subclass_of_intersection.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_subclass_of_intersection.sparql new file mode 100644 index 0000000..7482b5c --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_subclass_of_intersection.sparql @@ -0,0 +1,16 @@ +PREFIX pcl: +PREFIX owl: +PREFIX rdfs: +PREFIX rdf: + +CONSTRUCT { + ?class rdfs:subClassOf ?otherClass . + ?otherClass ?p ?o . +} +WHERE { + ?class a owl:Class ; + rdfs:subClassOf [ a owl:Class ; + owl:intersectionOf [ rdf:rest*/rdf:first ?otherClass ] ] . + ?otherClass ?p ?o . + FILTER( strstarts(str(?class),str(pcl:)) ) +} diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_test.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_test.sparql new file mode 100644 index 0000000..e54e758 --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_test.sparql @@ -0,0 +1,23 @@ +PREFIX : +PREFIX rdfs: +PREFIX owl: + +CONSTRUCT { + ?x a owl:Class . + ?x owl:equivalentClass ?y . + ?x rdfs:label ?l . + ?x rdfs:comment ?c . + ?y rdfs:label ?l2 . +} + +WHERE { + ?x a owl:Class . + ?x rdfs:subClassOf ?y . + ?x rdfs:label ?l . + ?x rdfs:comment ?c . + ?y rdfs:label ?l2 . + FILTER(isIRI(?x)) + FILTER(isIRI(?y)) +} + +LIMIT 10000 \ No newline at end of file diff --git a/cl_kb_pipeline/config/dumps/sparql/construct_test2.sparql b/cl_kb_pipeline/config/dumps/sparql/construct_test2.sparql new file mode 100644 index 0000000..dc48f88 --- /dev/null +++ b/cl_kb_pipeline/config/dumps/sparql/construct_test2.sparql @@ -0,0 +1,16 @@ +PREFIX : +PREFIX rdfs: +PREFIX owl: + +CONSTRUCT { + ?x ?p ?y . +} + +WHERE { + ?x ?p ?y . + FILTER(isIRI(?x)) + FILTER(isIRI(?p)) + FILTER(isIRI(?y)) +} + +LIMIT 10000 \ No newline at end of file diff --git a/cl_kb_pipeline/config/update-prod/config.env b/cl_kb_pipeline/config/update-prod/config.env new file mode 100644 index 0000000..4fa853e --- /dev/null +++ b/cl_kb_pipeline/config/update-prod/config.env @@ -0,0 +1,3 @@ +server=http://obask-kb:7474 +user=neo4j +password=password diff --git a/cl_kb_pipeline/config/update-prod/pdb_set_indices.neo4j b/cl_kb_pipeline/config/update-prod/pdb_set_indices.neo4j new file mode 100644 index 0000000..85cd2db --- /dev/null +++ b/cl_kb_pipeline/config/update-prod/pdb_set_indices.neo4j @@ -0,0 +1,11 @@ +{ + "statements" : [ { + "statement" : "CREATE INDEX ON :Individual(short_form)" + } , { + "statement" : "CREATE INDEX ON :Class(short_form)" + } , { + "statement" : "CREATE INDEX ON :Entity(short_form)" + } , { + "statement" : "CREATE INDEX ON :Template(short_form)" + } ] +} diff --git a/cl_kb_pipeline/config/updatetriplestore/config.env b/cl_kb_pipeline/config/updatetriplestore/config.env new file mode 100644 index 0000000..1e52355 --- /dev/null +++ b/cl_kb_pipeline/config/updatetriplestore/config.env @@ -0,0 +1,3 @@ +SERVER=http://triplestore:8080 +EXPORT_KB_TO_OWL=false +REPO_NAME=obask diff --git a/cl_kb_pipeline/config/updatetriplestore/rdf4j.txt b/cl_kb_pipeline/config/updatetriplestore/rdf4j.txt new file mode 100644 index 0000000..aab71b2 --- /dev/null +++ b/cl_kb_pipeline/config/updatetriplestore/rdf4j.txt @@ -0,0 +1,17 @@ +connect http://triplestore:8080/rdf4j-server +connect http://triplestore:8080/rdf4j-server +show repositories +drop obask. +yes +create memory. +obask +OBASK integration layer triplestore +10000 +true +0 +org.eclipse.rdf4j.query.algebra.evaluation.impl.StrictEvaluationStrategyFactory +show repositories +open obask . +select * where {?s ?p ?o } LIMIT 5. +close. +quit. diff --git a/cl_kb_pipeline/docker-compose.yml b/cl_kb_pipeline/docker-compose.yml new file mode 100644 index 0000000..5a441e3 --- /dev/null +++ b/cl_kb_pipeline/docker-compose.yml @@ -0,0 +1,121 @@ +version: '3.8' + +services: + triplestore: + image: eclipse/rdf4j-workbench:3.7.7 + container_name: triplestore + environment: + - JAVA_OPTS=-Xms1G -Xmx5G + ports: + - 8080:8080 + volumes: + - triplestore_data:/var/rdf4j + obask-kb: + image: ghcr.io/obasktools/obask-kb:latest + container_name: obask-kb + environment: + - NEO4J_AUTH=neo4j/neo + - NEO4J_dbms_read__only=false + - NEO4J_dbms_memory_heap_maxSize=4G + - NEO4J_dbms_memory_heap_initial__size=1G + ports: + - 7474:7474 + - 7687:7687 + links: + - solr + depends_on: + obask-dumps: + condition: service_completed_successfully + volumes: + - obask_data:/input + healthcheck: + test: [ "CMD", "wget", "-O", "-", "http://obask-kb:7474" ] + interval: 18s + timeout: 12s + retries: 20 + start_period: 3s + obask-collectdata: + image: ghcr.io/obasktools/pipeline-collectdata:latest + container_name: collectdata + depends_on: + - triplestore + volumes: + - ./config/collectdata:/opt/conf_base/config/collectdata + - obask_data:/out + obask-updatetriplestore: + image: ghcr.io/obasktools/pipeline-updatetriplestore:latest + container_name: updatetriplestore + depends_on: + obask-collectdata: + condition: service_completed_successfully + links: + - triplestore + environment: + - SERVER=http://triplestore:8080 + volumes: + - ./config/updatetriplestore:/opt/conf_base/config/updatetriplestore + - obask_data:/data + obask-dumps: + image: ghcr.io/obasktools/pipeline-dumps:latest + container_name: dumps + depends_on: + obask-updatetriplestore: + condition: service_completed_successfully + links: + - triplestore + volumes: + - ./config/dumps:/opt/conf_base/config/dumps + - obask_data:/out + obask-updateprod: + image: ghcr.io/obasktools/pipeline-updateprod:latest + container_name: updateprod + depends_on: + obask-kb: + condition: service_healthy + links: + - obask-kb + environment: + - password=neo4j/neo + - server=http://obask-kb:7474 + volumes: + - ./config/update-prod:/opt/conf_base/config/update-prod + - obask_data:/input + solr: + image: solr:8.11 + container_name: solr + ports: + - 8993:8983 + depends_on: + - obask-dumps + links: + - obask-dumps + volumes: + - solr_data:/var/solr + entrypoint: + - bash + - "-c" + - "precreate-core ontology; precreate-core bdsdump; exec solr -f" + obask-updatesolr: + image: ghcr.io/obasktools/pipeline-updatesolr:latest + container_name: updatesolr + links: + - solr + volumes: + - obask_data:/data + depends_on: + obask-dumps: + condition: service_completed_successfully + obask-ontology-search: + image: ghcr.io/obasktools/ontology-search:latest + container_name: ontology-search + ports: + - 8007:8007 + depends_on: + - solr + - obask-updatesolr + links: + - solr +volumes: + obask_data: + solr_data: + triplestore_data: \ No newline at end of file diff --git a/cl_kb_pipeline/src/__init__.py b/cl_kb_pipeline/src/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/cl_kb_pipeline/src/test_neo2owl_config.py b/cl_kb_pipeline/src/test_neo2owl_config.py new file mode 100644 index 0000000..1090cdc --- /dev/null +++ b/cl_kb_pipeline/src/test_neo2owl_config.py @@ -0,0 +1,5 @@ +from utils.schema_test_tools import test_local + +test_local(path_to_schema_dir='config/dumps/', + schema_file='neo4j2owl_config_schema.json', + path_to_test_dir='config/dumps/') diff --git a/cl_kb_pipeline/src/utils/__init__.py b/cl_kb_pipeline/src/utils/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/cl_kb_pipeline/src/utils/schema_test_tools.py b/cl_kb_pipeline/src/utils/schema_test_tools.py new file mode 100644 index 0000000..e236d71 --- /dev/null +++ b/cl_kb_pipeline/src/utils/schema_test_tools.py @@ -0,0 +1,118 @@ +import json +import sys +from jsonschema import Draft4Validator, RefResolver, SchemaError +import os +import glob +from ruamel.yaml import YAML, YAMLError +import warnings +from pathlib import Path + + +def get_json_from_file(filename): + """Loads json from a file. + """ + with open(filename, 'r') as f: + try: + fc = f.read() + except Exception as exc: + warnings.warn('Failed to open ' + filename + ' as JSON') + return json.loads(fc) + + +def get_yaml_from_file(filename): + """Loads YAML from a file. + """ + ryaml = YAML(typ='safe') + with open(filename) as stream: + try: + y = ryaml.load(stream) + except YAMLError as exc: + warnings.warn('Failed to open ' + filename + ' as YAML') + return y + + +def get_validator(filename, base_uri=''): + """Load schema from JSON file; + Check whether it's a valid schema; + Return a Draft4Validator object. + Optionally specify a base URI for relative path + resolution of JSON pointers (This is especially useful + for local resolution via base_uri of form file://{some_path}/) + """ + + schema = get_json_from_file(filename) + try: + # Check schema via class method call. Works, despite IDE complaining + # However, it appears that this doesn't catch every schema issue. + Draft4Validator.check_schema(schema) + print("%s is a valid JSON schema" % filename) + except SchemaError: + raise + if base_uri: + resolver = RefResolver(base_uri=base_uri, + referrer=filename) + else: + resolver = None + return Draft4Validator(schema=schema, + resolver=resolver) + + +def validate(validator, instance): + """Validate an instance of a schema and report errors.""" + if validator.is_valid(instance): + print("Validation Passes") + return True + else: + es = validator.iter_errors(instance) + recurse_through_errors(es) + # print("Validation Fails") + sys.exit("Validation Fails") + return False + + +def recurse_through_errors(es, level=0): + """Recurse through errors posting message + and schema path until context is empty""" + # Assuming blank context is a sufficient escape clause here. + for e in es: + warnings.warn( + "***" * level + " subschema level " + str(level) + "\t".join([str(e.message), + "Path to error:" + str( + e.absolute_schema_path)]) + "\n") + if e.context: + level += 1 + recurse_through_errors(e.context, level=level) + + +def test_local(path_to_schema_dir, schema_file, path_to_test_dir, load_yaml=True): + """Tests all instances in a test_folder against a single schema. + Assumes all schema files in single dir. + Assumes all *.json files in the test_dir should validate against the schema. + * path_to_schema_dir: Absolute or relative path to schema dir + * schema_file: schema file name + * test_dir: path to test directory (absolute or local to schema dir) + """ + file_ext = 'json' + loader = get_json_from_file + if load_yaml: + file_ext = 'yaml' + loader = get_yaml_from_file + # Getting script directory, schema directory and test directory + script_folder = Path(os.path.dirname(os.path.realpath(__file__))).parent + schema_dir = Path(os.path.dirname(path_to_schema_dir)) + test_dir = Path(os.path.dirname(path_to_test_dir)) + # Checking whether schema directory and test directory are in the parent directory of script directory + if not os.path.exists(os.path.join(script_folder.parent, schema_dir)): + raise Exception("Please provide valid path_to_schema_dir") + if not os.path.exists(os.path.join(script_folder.parent, test_dir)): + raise Exception("Please provide valid path_to_test_dir") + else: + sv = get_validator(os.path.join(script_folder.parent, schema_dir, schema_file)) + test_dir_files = ''.join(['/*.', file_ext]) + test_files = glob.glob(pathname=os.path.join(script_folder.parent, test_dir) + test_dir_files) + # print("Found test files: %s in %s" % (str(test_files), path_to_test_dir)) + for instance_file in test_files: + print(instance_file) + i = loader(instance_file) + print("Testing: %s" % instance_file) + validate(sv, i) From ec62b2dcfc37d2d95099d97052e89239e5caaaa5 Mon Sep 17 00:00:00 2001 From: ugur Date: Thu, 4 Apr 2024 14:04:22 +0100 Subject: [PATCH 05/18] Added test file --- .../src/curated_data/HCA-CxG-retina.csv | 25 +++++++++++++++++++ 1 file changed, 25 insertions(+) create mode 100644 anndata2rdf/src/curated_data/HCA-CxG-retina.csv diff --git a/anndata2rdf/src/curated_data/HCA-CxG-retina.csv b/anndata2rdf/src/curated_data/HCA-CxG-retina.csv new file mode 100644 index 0000000..2690465 --- /dev/null +++ b/anndata2rdf/src/curated_data/HCA-CxG-retina.csv @@ -0,0 +1,25 @@ +Dataset,CxG link,Reference,Bionetworks reference,Standard category cell_type present? (T/F),Author Category Cell Type Field Name,Content,Value Type(s),Notes +Retina,https://cellxgene.cziscience.com/e/d5c67a4e-a8d9-456d-a273-fa01adb1b308.cxg/,https://doi.org/10.15252/embj.2018100811,retina,T,author_cell_type,cell types,full names, +Retina,https://cellxgene.cziscience.com/e/d5c67a4e-a8d9-456d-a273-fa01adb1b308.cxg/,https://doi.org/10.1038/s41467-019-12780-8,retina,T,CellType,cell types,"full names, abbreviations", +Bipolar cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/8623d55f-d91c-41c2-ae68-ed2072fd268d.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,author_cell_type,cell types,abbreviations, +Bipolar cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/8623d55f-d91c-41c2-ae68-ed2072fd268d.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" +Non-neuronal cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/bc7260e0-54cf-4b0b-823d-93f5b850f757.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,author_cell_type,cell types,full names, +Non-neuronal cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/bc7260e0-54cf-4b0b-823d-93f5b850f757.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" +Amacrine cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/5cdbb2ea-c622-466d-9ead-7884ad8cb99f.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,author_cell_type,cell types,abbreviations,"e.g., Gaba1, Gaba2, Gly1, Gly2" +Amacrine cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/5cdbb2ea-c622-466d-9ead-7884ad8cb99f.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" +Retinal ganglion cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/d319af7f-be2e-441e-8caa-3b8a88480e89.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,F,author_cell_type,cell types,abbreviations, +Retinal ganglion cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/d319af7f-be2e-441e-8caa-3b8a88480e89.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,F,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" +Photoreceptor cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/7b75b2c4-6d99-40be-9a61-391455d859e6.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,author_cell_type,cell types,full names, +Photoreceptor cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/7b75b2c4-6d99-40be-9a61-391455d859e6.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" +Horizontal cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/2f6a20f1-173d-4b8d-860b-c47ffea120fa.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,F,author_cell_type,cell types,abbreviations,"Only 2: H1, H2" +Horizontal cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/2f6a20f1-173d-4b8d-860b-c47ffea120fa.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,F,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" +All cell types of human eye,https://cellxgene.cziscience.com/e/e6dad530-418b-47f9-af6e-472e56a7b314.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,T,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0, etc." +Rod cells of human eye,https://cellxgene.cziscience.com/e/389bfbb9-8ef1-4582-8c41-410131c3d0eb.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,F,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0" +Bipolar cells of human eye,https://cellxgene.cziscience.com/e/4e38f019-f8e8-44ae-ad32-ba500de6f64c.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,T,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0, etc." +Non-neuronal cells of human eye,https://cellxgene.cziscience.com/e/ab5b2256-b209-48b5-a801-c5d9a8c0de56.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,T,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0, etc." +Amacrine cells of human eye,https://cellxgene.cziscience.com/e/f8c77961-67a7-4161-b8c2-61c3f917b54f.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,F,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0, etc." +Horizontal cells of human eye,https://cellxgene.cziscience.com/e/c3d381b2-3104-444e-8ad5-d3524407bbb6.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,T,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0" +Retinal ganglion cells of human eye,https://cellxgene.cziscience.com/e/cec9f9a5-8832-437d-99af-fb8237cde54b.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,T,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0, etc." +Retinal pigment epithelial cells of human eye,https://cellxgene.cziscience.com/e/9cfee1e6-b24f-433d-a269-f01841655d6a.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,F,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0" +Cone cells of human eye,https://cellxgene.cziscience.com/e/d95ab381-2b7c-4885-b168-0097ed4e397f.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,T,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0, etc." +Myeloid cells of human eye,https://cellxgene.cziscience.com/e/de17ac25-550a-4018-be75-bbb485a0636e.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,F,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0" \ No newline at end of file From a4b248dfd0d3a12b8fdc088dbf028c8942c43974 Mon Sep 17 00:00:00 2001 From: ugur Date: Thu, 4 Apr 2024 14:12:54 +0100 Subject: [PATCH 06/18] Updated test file --- anndata2rdf/src/curated_data/HCA-CxG-retina.csv | 12 +----------- 1 file changed, 1 insertion(+), 11 deletions(-) diff --git a/anndata2rdf/src/curated_data/HCA-CxG-retina.csv b/anndata2rdf/src/curated_data/HCA-CxG-retina.csv index 2690465..7ce6269 100644 --- a/anndata2rdf/src/curated_data/HCA-CxG-retina.csv +++ b/anndata2rdf/src/curated_data/HCA-CxG-retina.csv @@ -12,14 +12,4 @@ Retinal ganglion cells of the human fovea and peripheral retina,https://cellxgen Photoreceptor cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/7b75b2c4-6d99-40be-9a61-391455d859e6.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,author_cell_type,cell types,full names, Photoreceptor cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/7b75b2c4-6d99-40be-9a61-391455d859e6.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" Horizontal cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/2f6a20f1-173d-4b8d-860b-c47ffea120fa.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,F,author_cell_type,cell types,abbreviations,"Only 2: H1, H2" -Horizontal cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/2f6a20f1-173d-4b8d-860b-c47ffea120fa.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,F,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" -All cell types of human eye,https://cellxgene.cziscience.com/e/e6dad530-418b-47f9-af6e-472e56a7b314.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,T,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0, etc." -Rod cells of human eye,https://cellxgene.cziscience.com/e/389bfbb9-8ef1-4582-8c41-410131c3d0eb.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,F,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0" -Bipolar cells of human eye,https://cellxgene.cziscience.com/e/4e38f019-f8e8-44ae-ad32-ba500de6f64c.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,T,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0, etc." -Non-neuronal cells of human eye,https://cellxgene.cziscience.com/e/ab5b2256-b209-48b5-a801-c5d9a8c0de56.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,T,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0, etc." -Amacrine cells of human eye,https://cellxgene.cziscience.com/e/f8c77961-67a7-4161-b8c2-61c3f917b54f.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,F,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0, etc." -Horizontal cells of human eye,https://cellxgene.cziscience.com/e/c3d381b2-3104-444e-8ad5-d3524407bbb6.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,T,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0" -Retinal ganglion cells of human eye,https://cellxgene.cziscience.com/e/cec9f9a5-8832-437d-99af-fb8237cde54b.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,T,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0, etc." -Retinal pigment epithelial cells of human eye,https://cellxgene.cziscience.com/e/9cfee1e6-b24f-433d-a269-f01841655d6a.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,F,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0" -Cone cells of human eye,https://cellxgene.cziscience.com/e/d95ab381-2b7c-4885-b168-0097ed4e397f.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,T,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0, etc." -Myeloid cells of human eye,https://cellxgene.cziscience.com/e/de17ac25-550a-4018-be75-bbb485a0636e.cxg/,https://doi.org/10.1016/j.celrep.2019.12.082,retina,F,author_cell_type (*see Notes),,,"*author_cell_type contains only floats: 1.0, 2.0, 3.0" \ No newline at end of file +Horizontal cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/2f6a20f1-173d-4b8d-860b-c47ffea120fa.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,F,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" \ No newline at end of file From bc0ee6bbe25e8189b973f69b1a8aa7890123c10f Mon Sep 17 00:00:00 2001 From: ugur Date: Fri, 5 Apr 2024 21:12:37 +0100 Subject: [PATCH 07/18] Updated Dockerfile --- anndata2rdf/Dockerfile | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/anndata2rdf/Dockerfile b/anndata2rdf/Dockerfile index 5d4c6b5..b58789f 100644 --- a/anndata2rdf/Dockerfile +++ b/anndata2rdf/Dockerfile @@ -2,7 +2,8 @@ FROM python:3.9 SHELL ["/bin/bash", "-c"] -RUN apt-get update && apt-get install -y build-essential graphviz libgraphviz-dev pkg-config && apt-get clean && rm -rf /var/lib/apt/lists/* +RUN apt-get update && apt-get install -y build-essential graphviz libgraphviz-dev pkg-config zip unzip tar ninja-build \ + && apt-get clean && rm -rf /var/lib/apt/lists/* WORKDIR /app @@ -11,6 +12,10 @@ ENV PATH="$VENV/bin:$PATH" RUN python -m venv $VENV +RUN python3 -m venv $VENV + +RUN pip3 install --upgrade pip wheel + COPY requirements.txt ./ RUN pip install -r requirements.txt From 22f25e32a3cc3c0822bd75abc4c1695e4bacc3cd Mon Sep 17 00:00:00 2001 From: ugur Date: Fri, 5 Apr 2024 21:16:18 +0100 Subject: [PATCH 08/18] Updated Dockerfile --- .github/workflows/docker-publish.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/docker-publish.yml b/.github/workflows/docker-publish.yml index 4875d16..abe5a08 100644 --- a/.github/workflows/docker-publish.yml +++ b/.github/workflows/docker-publish.yml @@ -54,7 +54,7 @@ jobs: - name: Build and push Docker image uses: docker/build-push-action@ad44023a93711e3deb337508980b4b5e9bcdc5dc with: - context: "{{defaultContext}}:anndata2rdf" + context: "./anndata2rdf/" push: true platforms: linux/amd64,linux/arm64 tags: ${{ steps.meta.outputs.tags }} From f597ad955e983332e0d4b6e7d8c8da8334163cd3 Mon Sep 17 00:00:00 2001 From: ugur Date: Sun, 12 May 2024 20:01:23 +0100 Subject: [PATCH 09/18] Refactored dataset download logic --- anndata2rdf/Dockerfile | 28 ++++++----- anndata2rdf/requirements.txt | 5 +- anndata2rdf/src/csv_parser.py | 3 +- ...s - Brain_CxG_Author_Category_Filtered.csv | 18 +++++++ .../src/curated_data/HCA-CxG-retina.csv | 15 ------ anndata2rdf/src/generate_rdf.py | 2 +- anndata2rdf/src/process.py | 30 ++++++++++-- anndata2rdf/src/pull_anndata.py | 49 +++++++++++++++++-- .../config/collectdata/vfb_fullontologies.txt | 4 +- cl_kb_pipeline/docker-compose.yml | 14 +++++- 10 files changed, 123 insertions(+), 45 deletions(-) create mode 100644 anndata2rdf/src/curated_data/CxG author category field names - Brain_CxG_Author_Category_Filtered.csv delete mode 100644 anndata2rdf/src/curated_data/HCA-CxG-retina.csv diff --git a/anndata2rdf/Dockerfile b/anndata2rdf/Dockerfile index b58789f..dec8360 100644 --- a/anndata2rdf/Dockerfile +++ b/anndata2rdf/Dockerfile @@ -1,24 +1,26 @@ -FROM python:3.9 +FROM python:3.10 SHELL ["/bin/bash", "-c"] -RUN apt-get update && apt-get install -y build-essential graphviz libgraphviz-dev pkg-config zip unzip tar ninja-build \ - && apt-get clean && rm -rf /var/lib/apt/lists/* +RUN apt-get update && apt-get install -y build-essential graphviz libgraphviz-dev pkg-config libhdf5-dev && apt-get clean && rm \ + -rf /var/lib/apt/lists/* WORKDIR /app -ENV VENV="/opt/env" -ENV PATH="$VENV/bin:$PATH" - -RUN python -m venv $VENV - -RUN python3 -m venv $VENV - -RUN pip3 install --upgrade pip wheel +#ENV VENV="/opt/env" +#ENV PATH="$VENV/bin:$PATH" +# +#RUN python3 -m venv $VENV COPY requirements.txt ./ -RUN pip install -r requirements.txt +RUN pip3 install --upgrade pip +RUN pip3 install -r requirements.txt + +RUN mkdir -p src/config src/curated_data src/dataset src/graph -COPY src/ ./src +COPY src/csv_parser.py ./src +COPY src/pull_anndata.py ./src +COPY src/generate_rdf.py ./src +COPY src/process.py ./src CMD ["python", "src/process.py"] diff --git a/anndata2rdf/requirements.txt b/anndata2rdf/requirements.txt index 5ba4740..28e9b64 100644 --- a/anndata2rdf/requirements.txt +++ b/anndata2rdf/requirements.txt @@ -1,4 +1,3 @@ -cellxgene-census==1.11.1 -pandasaurus-cxg~=0.1.11 -pandas~=2.2.1 +pandasaurus-cxg +pandas PyYAML~=6.0.1 \ No newline at end of file diff --git a/anndata2rdf/src/csv_parser.py b/anndata2rdf/src/csv_parser.py index 668db2d..42668c2 100644 --- a/anndata2rdf/src/csv_parser.py +++ b/anndata2rdf/src/csv_parser.py @@ -12,7 +12,8 @@ def generate_yaml_data(data): - grouped_data = data.groupby("CxG link") + filtered_df = data[data["Content"] == "cell types"] + grouped_data = filtered_df.groupby("h5ad link") _yaml_data = [] for link, group_df in grouped_data: author_cell_type_list = [ diff --git a/anndata2rdf/src/curated_data/CxG author category field names - Brain_CxG_Author_Category_Filtered.csv b/anndata2rdf/src/curated_data/CxG author category field names - Brain_CxG_Author_Category_Filtered.csv new file mode 100644 index 0000000..4295bd0 --- /dev/null +++ b/anndata2rdf/src/curated_data/CxG author category field names - Brain_CxG_Author_Category_Filtered.csv @@ -0,0 +1,18 @@ +Dataset,Full name dataset,CxG link,h5ad link,Reference_DOI,Bionetworks reference,Standard category present? (T/F),Standard category cell_type present? (T/F),Author Category Cell Type Field Name,Content,Value type(s),Notes,Study Short Name,CxG Dataset Collection,Is the dataset Normal or Normal/Diseased,Stage +Dissection: Primary visual cortex(V1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/8d1dd010-5cbc-43fb-83f8-e0de8e8517da.cxg/,https://datasets.cellxgene.cziscience.com/325567b8-e698-48ab-9969-ab0b1a2bbb2f.h5ad,DOI: 10.1126/science.adf6812,,T,T,Class,cell types,normal,"excitatory, inhibitory, non-neuronal",Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary visual cortex(V1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/8d1dd010-5cbc-43fb-83f8-e0de8e8517da.cxg/,https://datasets.cellxgene.cziscience.com/325567b8-e698-48ab-9969-ab0b1a2bbb2f.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_cluster,cell types,abbreviations,"Astro_1, Astro_2, Astro_3, Astro_4",Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary visual cortex(V1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/8d1dd010-5cbc-43fb-83f8-e0de8e8517da.cxg/,https://datasets.cellxgene.cziscience.com/325567b8-e698-48ab-9969-ab0b1a2bbb2f.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_subclass,cell types,"abbreviation, normal","Astro_1, Astro_2, Astro_3, Astro_4",Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary visual cortex(V1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/8d1dd010-5cbc-43fb-83f8-e0de8e8517da.cxg/,https://datasets.cellxgene.cziscience.com/325567b8-e698-48ab-9969-ab0b1a2bbb2f.h5ad,DOI: 10.1126/science.adf6812,,T,T,Layer,Other,"abbreviation, normal","All, L5",Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary visual cortex(V1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/8d1dd010-5cbc-43fb-83f8-e0de8e8517da.cxg/,https://datasets.cellxgene.cziscience.com/325567b8-e698-48ab-9969-ab0b1a2bbb2f.h5ad,DOI: 10.1126/science.adf6812,,T,T,Source,other,abbreviations,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary visual cortex(V1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/8d1dd010-5cbc-43fb-83f8-e0de8e8517da.cxg/,https://datasets.cellxgene.cziscience.com/325567b8-e698-48ab-9969-ab0b1a2bbb2f.h5ad,DOI: 10.1126/science.adf6812,,T,T,Subregion,other,abbreviations,"V1C, V1C_L5, V1_L5",Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary visual cortex(V1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/8d1dd010-5cbc-43fb-83f8-e0de8e8517da.cxg/,https://datasets.cellxgene.cziscience.com/325567b8-e698-48ab-9969-ab0b1a2bbb2f.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,"abbreviations, normal","Astro_1, Astro_2, Astro_3, Astro_4",Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary visual cortex(V1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/8d1dd010-5cbc-43fb-83f8-e0de8e8517da.cxg/,https://datasets.cellxgene.cziscience.com/325567b8-e698-48ab-9969-ab0b1a2bbb2f.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,"abbreviations, normal","Astro, Chandelier, Endo, L2/3 IT, L4 IT, L5 ET, L5 IT, L5/6 NP, L6 CT, L6 IT, L6 IT Car3, L6b, Lamp5, Lamp5 Lhx6, Micro/PVM, OPC, Oligo, Pax6, Pvalb, Sncg, Sst, Sst Chodl, VLMC, Vip",Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_cluster,cell types,abbreviations,Chandelier_1 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 Sst_33 Sst_34 Sst_35 Sst_36 Sst_37,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_subclass,cell types,"abbreviations, normal",Chandelier Pvalb Sst Sst Chodl,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,Layer,other,"abbreviations, normal",All L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,Location,other,normal,caudal lateral caudal medial central lateral central lateral central medial rostral medial rostral middle,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,Region,other,abbreviations,A1 ACC ANG DLPFC M1 MTG S1 V1,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,Source,other,abbreviations,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,Subregion,other,abbreviations,A1C ACC ANG DLPFC M1C MTG S1C V1C L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,"abbreviations, normal",Chandelier_1 Chandelier_2 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Pvalb_10 Pvalb_11 Pvalb_12 Pvalb_13 Pvalb_14 Pvalb_15 Pvalb_16 Pvalb_17 Sst Chodl_1 Sst Chodl_2 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 Sst_33 Sst_34 Sst_35 Sst_36 Sst_37 Sst_38,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,"abbreviations, normal",Chandelier Pvalb Sst Sst Chodl,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult \ No newline at end of file diff --git a/anndata2rdf/src/curated_data/HCA-CxG-retina.csv b/anndata2rdf/src/curated_data/HCA-CxG-retina.csv deleted file mode 100644 index 7ce6269..0000000 --- a/anndata2rdf/src/curated_data/HCA-CxG-retina.csv +++ /dev/null @@ -1,15 +0,0 @@ -Dataset,CxG link,Reference,Bionetworks reference,Standard category cell_type present? (T/F),Author Category Cell Type Field Name,Content,Value Type(s),Notes -Retina,https://cellxgene.cziscience.com/e/d5c67a4e-a8d9-456d-a273-fa01adb1b308.cxg/,https://doi.org/10.15252/embj.2018100811,retina,T,author_cell_type,cell types,full names, -Retina,https://cellxgene.cziscience.com/e/d5c67a4e-a8d9-456d-a273-fa01adb1b308.cxg/,https://doi.org/10.1038/s41467-019-12780-8,retina,T,CellType,cell types,"full names, abbreviations", -Bipolar cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/8623d55f-d91c-41c2-ae68-ed2072fd268d.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,author_cell_type,cell types,abbreviations, -Bipolar cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/8623d55f-d91c-41c2-ae68-ed2072fd268d.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" -Non-neuronal cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/bc7260e0-54cf-4b0b-823d-93f5b850f757.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,author_cell_type,cell types,full names, -Non-neuronal cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/bc7260e0-54cf-4b0b-823d-93f5b850f757.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" -Amacrine cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/5cdbb2ea-c622-466d-9ead-7884ad8cb99f.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,author_cell_type,cell types,abbreviations,"e.g., Gaba1, Gaba2, Gly1, Gly2" -Amacrine cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/5cdbb2ea-c622-466d-9ead-7884ad8cb99f.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" -Retinal ganglion cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/d319af7f-be2e-441e-8caa-3b8a88480e89.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,F,author_cell_type,cell types,abbreviations, -Retinal ganglion cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/d319af7f-be2e-441e-8caa-3b8a88480e89.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,F,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" -Photoreceptor cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/7b75b2c4-6d99-40be-9a61-391455d859e6.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,author_cell_type,cell types,full names, -Photoreceptor cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/7b75b2c4-6d99-40be-9a61-391455d859e6.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,T,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" -Horizontal cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/2f6a20f1-173d-4b8d-860b-c47ffea120fa.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,F,author_cell_type,cell types,abbreviations,"Only 2: H1, H2" -Horizontal cells of the human fovea and peripheral retina,https://cellxgene.cziscience.com/e/2f6a20f1-173d-4b8d-860b-c47ffea120fa.cxg/,https://doi.org/10.1038/s41598-020-66092-9,retina,F,suspension_enriched_cell_types,cell types,full names,"Only 2: na, retinal ganglion cell" \ No newline at end of file diff --git a/anndata2rdf/src/generate_rdf.py b/anndata2rdf/src/generate_rdf.py index f4d3062..807bdba 100644 --- a/anndata2rdf/src/generate_rdf.py +++ b/anndata2rdf/src/generate_rdf.py @@ -32,7 +32,7 @@ def generate_rdf_graph( with open( os.path.join( config_dir, - "rdf_config.yaml", + "cxg_author_cell_type.yaml", ), "r", ) as file: diff --git a/anndata2rdf/src/process.py b/anndata2rdf/src/process.py index 69d073e..37dacb2 100644 --- a/anndata2rdf/src/process.py +++ b/anndata2rdf/src/process.py @@ -3,14 +3,15 @@ import sys from csv_parser import generate_author_cell_type_config, write_yaml_file -from pull_anndata import download_dataset_with_id, get_dataset_dict, delete_file +from pull_anndata import download_dataset_with_id, get_dataset_dict, delete_file, download_dataset_with_url, \ + get_dataset_id_from_h5ad_link from generate_rdf import generate_rdf_graph logger = logging.getLogger(__name__) logging.basicConfig(level=logging.WARNING) stdout_handler = logging.StreamHandler(sys.stdout) stdout_handler.setLevel(logging.INFO) -formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') +formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s") stdout_handler.setFormatter(formatter) logger.addHandler(stdout_handler) @@ -29,15 +30,34 @@ ) write_yaml_file(cxg_author_cell_type_yaml, output_file_path) +# datasets = get_dataset_dict( +# [ +# { +# "CxG_link": "https://cellxgene.cziscience.com/e/8e10f1c4-8e98-41e5-b65f-8cd89a887122.cxg/", +# "author_cell_type_list": [ +# "ROIGroup", +# "ROIGroupCoarse", +# "ROIGroupFine", +# "cluster_id", +# "dissection", +# "roi", +# "sample_id", +# "subcluster_id", +# "supercluster_term", +# ], +# } +# ] +# ) datasets = get_dataset_dict(cxg_author_cell_type_yaml) for dataset, author_cell_types in datasets.items(): - dataset_path = download_dataset_with_id(dataset) + # dataset_path = download_dataset_with_id(dataset) + dataset_path = download_dataset_with_url(dataset) generate_rdf_graph( dataset_path, author_cell_types, os.path.join( os.path.join(os.path.dirname(os.path.abspath(__file__)), GRAPH_DIRECTORY), - dataset, + get_dataset_id_from_h5ad_link(dataset), ), ) - delete_file(dataset_path) + # delete_file(dataset_path) diff --git a/anndata2rdf/src/pull_anndata.py b/anndata2rdf/src/pull_anndata.py index 96edf03..317cb2b 100644 --- a/anndata2rdf/src/pull_anndata.py +++ b/anndata2rdf/src/pull_anndata.py @@ -1,9 +1,9 @@ import logging import os from typing import Dict, List, Optional, Union -import yaml -import cellxgene_census +import requests +import yaml logging.basicConfig(level=logging.WARNING) @@ -38,6 +38,42 @@ def download_dataset_with_id(dataset_id: str, file_path: Optional[str] = None) - return anndata_file_path +def download_dataset_with_url(dataset_url: str, file_path: Optional[str] = None) -> str: + """ + Download an AnnData dataset with the specified url. + + Args: + dataset_url (str): The url of the dataset to download. + file_path (Optional[str], optional): The file path to save the downloaded AnnData. If not provided, + the dataset_id will be used as the file name. Defaults to None. + + Returns: + str: The path to the downloaded file + """ + + anndata_file_path = f"{get_dataset_id_from_h5ad_link(dataset_url)}.h5ad" if file_path is None else file_path + anndata_file_path = os.path.join( + os.path.dirname(os.path.abspath(__file__)), + os.path.join("dataset", anndata_file_path), + ) + if os.path.exists(anndata_file_path): + print("File already exists. Skipping download.") + else: + + response = requests.get(dataset_url) + if response.status_code == 200: + with open(anndata_file_path, 'wb') as f: + f.write(response.content) + print("File downloaded successfully.") + else: + print("Failed to download the file.") + return anndata_file_path + + +def get_dataset_id_from_h5ad_link(dataset_url): + return dataset_url.split('/')[-1].split('.')[0] + + def delete_file(file_name): try: os.remove(file_name) @@ -50,8 +86,11 @@ def get_dataset_dict(input_source: List[Dict]): cxg_dataset_dict = {} for config in input_source: cxg_link = config["CxG_link"] - cxg_id = get_dataset_id_from_link(cxg_link) - cxg_dataset_dict.update({cxg_id.split(".")[0]: config["author_cell_type_list"]}) + if cxg_link.endswith(".cxg"): + cxg_id = get_dataset_id_from_link(cxg_link) + cxg_dataset_dict.update({cxg_id.split(".")[0]: config["author_cell_type_list"]}) + else: + cxg_dataset_dict.update({cxg_link: config["author_cell_type_list"]}) return cxg_dataset_dict @@ -76,4 +115,4 @@ def read_yaml_config(config_file: str): ) datasets = get_dataset_dict(config_list) for dataset in datasets.keys(): - dataset_name = download_dataset_with_id(dataset) + dataset_name = download_dataset_with_url(dataset) diff --git a/cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt b/cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt index 5d68940..1082525 100644 --- a/cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt +++ b/cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt @@ -1 +1,3 @@ -http://purl.obolibrary.org/obo/cl/cl-base.owl \ No newline at end of file +http://purl.obolibrary.org/obo/cl/cl-base.owl +file:///out/local_ontologies/325567b8-e698-48ab-9969-ab0b1a2bbb2f.owl +file:///out/local_ontologies/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.owl \ No newline at end of file diff --git a/cl_kb_pipeline/docker-compose.yml b/cl_kb_pipeline/docker-compose.yml index 5a441e3..c45a962 100644 --- a/cl_kb_pipeline/docker-compose.yml +++ b/cl_kb_pipeline/docker-compose.yml @@ -1,6 +1,15 @@ version: '3.8' services: + anndata2rdf: + image: anndata2rdf:latest + container_name: anndata_to_rdf + volumes: + - ../anndata2rdf/src/config:/app/src/config + - ../anndata2rdf/src/curated_data:/app/src/curated_data + - ../anndata2rdf/src/dataset:/app/src/dataset + - obask_data:/app/src/graph + command: /bin/sh -c "python src/process.py && mkdir -p /app/src/graph/local_ontologies && mv /app/src/graph/*.owl /app/src/graph/local_ontologies/" triplestore: image: eclipse/rdf4j-workbench:3.7.7 container_name: triplestore @@ -38,7 +47,10 @@ services: image: ghcr.io/obasktools/pipeline-collectdata:latest container_name: collectdata depends_on: - - triplestore + triplestore: + condition: service_started + obask-collectdata: + condition: service_completed_successfully volumes: - ./config/collectdata:/opt/conf_base/config/collectdata - obask_data:/out From 71b625935775029dded0fc3be81163a135beed0c Mon Sep 17 00:00:00 2001 From: ugur Date: Sun, 12 May 2024 22:39:31 +0100 Subject: [PATCH 10/18] Updated configs --- ...s - Brain_CxG_Author_Category_Filtered.csv | 483 +++++++++++++++++- anndata2rdf/src/process.py | 2 +- .../config/dumps/neo4j2owl-config.yaml | 3 + cl_kb_pipeline/docker-compose.yml | 2 +- 4 files changed, 487 insertions(+), 3 deletions(-) diff --git a/anndata2rdf/src/curated_data/CxG author category field names - Brain_CxG_Author_Category_Filtered.csv b/anndata2rdf/src/curated_data/CxG author category field names - Brain_CxG_Author_Category_Filtered.csv index 4295bd0..7a2c6e3 100644 --- a/anndata2rdf/src/curated_data/CxG author category field names - Brain_CxG_Author_Category_Filtered.csv +++ b/anndata2rdf/src/curated_data/CxG author category field names - Brain_CxG_Author_Category_Filtered.csv @@ -15,4 +15,485 @@ Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals p Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,Source,other,abbreviations,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,Subregion,other,abbreviations,A1C ACC ANG DLPFC M1C MTG S1C V1C L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,"abbreviations, normal",Chandelier_1 Chandelier_2 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Pvalb_10 Pvalb_11 Pvalb_12 Pvalb_13 Pvalb_14 Pvalb_15 Pvalb_16 Pvalb_17 Sst Chodl_1 Sst Chodl_2 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 Sst_33 Sst_34 Sst_35 Sst_36 Sst_37 Sst_38,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult -Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,"abbreviations, normal",Chandelier Pvalb Sst Sst Chodl,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult \ No newline at end of file +Supercluster: MGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/9c63201d-bfd9-41a8-bbbc-18d947556f3d.cxg/,https://datasets.cellxgene.cziscience.com/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,"abbreviations, normal",Chandelier Pvalb Sst Sst Chodl,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary somatosensory cortex (S1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/93cb76aa-a84b-4a92-8e6c-66a914e26d4c.cxg/,https://datasets.cellxgene.cziscience.com/8b1e1941-cd79-48ba-81d1-43732803b9a5.h5ad,DOI: 10.1126/science.adf6812,,T,T,Class,cell types,normal,excitatory inhibitory non-neuronal,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary somatosensory cortex (S1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/93cb76aa-a84b-4a92-8e6c-66a914e26d4c.cxg/,https://datasets.cellxgene.cziscience.com/8b1e1941-cd79-48ba-81d1-43732803b9a5.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Astro_4 Astro_5 Chandelier_1 Endo_1 Endo_2 L2/3 IT_1 L2/3 IT_2 L2/3 IT_3 L2/3 IT_4 L2/3 IT_5 L2/3 IT_6 L4 IT_1 L4 IT_2 L4 IT_3 L4 IT_4 L4 IT_5 L4 IT_6 L5 ET_1 L5 ET_2 L5 ET_3 L5 ET_4 L5 ET_5 L5 ET_6 L5/6 NP_1 L5/6 NP_2 L5/6 NP_3 L5/6 NP_4 L5/6 NP_5 L5/6 NP_6 L6 CT_1 L6 CT_2 L6 CT_3 L6 IT Car3_1 L6 IT Car3_2 L6 IT_1 L6 IT_2 L6b_1 L6b_2 L6b_3 L6b_4 L6b_5 L6b_6 Lamp5_1 Lamp5_2 Lamp5_3 Lamp5_4 Lamp5_5 Lamp5_6 Lamp5_7 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Oligo_4 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sncg_8 Sst Chodl_1 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 Sst_33 Sst_34 Sst_35 Sst_36 Sst_37 VLMC_1 VLMC_2 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary somatosensory cortex (S1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/93cb76aa-a84b-4a92-8e6c-66a914e26d4c.cxg/,https://datasets.cellxgene.cziscience.com/8b1e1941-cd79-48ba-81d1-43732803b9a5.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary somatosensory cortex (S1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/93cb76aa-a84b-4a92-8e6c-66a914e26d4c.cxg/,https://datasets.cellxgene.cziscience.com/8b1e1941-cd79-48ba-81d1-43732803b9a5.h5ad,DOI: 10.1126/science.adf6812,,T,T,Layer,other,"abbreviations, normal",All L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary somatosensory cortex (S1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/93cb76aa-a84b-4a92-8e6c-66a914e26d4c.cxg/,https://datasets.cellxgene.cziscience.com/8b1e1941-cd79-48ba-81d1-43732803b9a5.h5ad,DOI: 10.1126/science.adf6812,,T,T,Source,other,abbreviations,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary somatosensory cortex (S1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/93cb76aa-a84b-4a92-8e6c-66a914e26d4c.cxg/,https://datasets.cellxgene.cziscience.com/8b1e1941-cd79-48ba-81d1-43732803b9a5.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Chandelier_1 Endo_1 L2/3 IT_1 L2/3 IT_2 L2/3 IT_3 L2/3 IT_4 L2/3 IT_5 L2/3 IT_6 L4 IT_1 L4 IT_2 L4 IT_3 L4 IT_4 L5 ET_1 L5 ET_2 L5 IT_1 L5 IT_2 L5 IT_3 L5 IT_4 L5/6 NP_1 L5/6 NP_2 L6 CT_1 L6 CT_2 L6 IT Car3_1 L6 IT_1 L6 IT_2 L6b_1 L6b_2 L6b_3 L6b_4 L6b_5 Lamp5 Lhx6_1 Lamp5 Lhx6_2 Lmpt5_1 Lmpt5_2 Lmpt5_3 Lmpt5_4 Lmpt5_5 Lmpt5_6 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pax6_5 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Pvalb_10 Pvalb_11 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sst Chodl_1 Sst Chodl_2 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 Sst_33 Sst_34 Sst_35 VLMC_1 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29 Vip_30 Vip_31,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary somatosensory cortex (S1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/93cb76aa-a84b-4a92-8e6c-66a914e26d4c.cxg/,https://datasets.cellxgene.cziscience.com/8b1e1941-cd79-48ba-81d1-43732803b9a5.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 ET L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Middle temporal gyrus (MTG),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/015c230d-650c-4527-870d-8a805849a382.cxg/,https://datasets.cellxgene.cziscience.com/5f36898f-78e7-4ba0-950e-a02beca606d4.h5ad,DOI: 10.1126/science.adf6812,,T,T,Class,cell types,normal,excitatory inhibitory non-neuronal,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Middle temporal gyrus (MTG),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/015c230d-650c-4527-870d-8a805849a382.cxg/,https://datasets.cellxgene.cziscience.com/5f36898f-78e7-4ba0-950e-a02beca606d4.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Astro_4 Astro_5 Chandelier_1 Endo_1 Endo_2 L2/3 IT_1 L2/3 IT_5 L2/3 IT_6 L4 IT_1 L4 IT_5 L5 ET_1 L5 ET_2 L5 ET_3 L5 IT_1 L5 IT_2 L5 IT_3 L5 IT_6 L5/6 NP_1 L5/6 NP_4 L5/6 NP_5 L6 CT_1 L6 CT_3 L6 IT Car3_1 L6 IT Car3_2 L6 IT_2 L6b_1 L6b_2 L6b_3 L6b_4 L6b_5 L6b_6 Lamp5_1 Lamp5_2 Lamp5_3 Lamp5_4 Lamp5_5 Lamp5_6 Lamp5_7 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Oligo_4 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sncg_8 Sst Chodl_1 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 VLMC_1 VLMC_2 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Middle temporal gyrus (MTG),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/015c230d-650c-4527-870d-8a805849a382.cxg/,https://datasets.cellxgene.cziscience.com/5f36898f-78e7-4ba0-950e-a02beca606d4.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 IT L5 ET L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Middle temporal gyrus (MTG),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/015c230d-650c-4527-870d-8a805849a382.cxg/,https://datasets.cellxgene.cziscience.com/5f36898f-78e7-4ba0-950e-a02beca606d4.h5ad,DOI: 10.1126/science.adf6812,,T,T,Layer,other,"abbreviations, normal",All L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Middle temporal gyrus (MTG),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/015c230d-650c-4527-870d-8a805849a382.cxg/,https://datasets.cellxgene.cziscience.com/5f36898f-78e7-4ba0-950e-a02beca606d4.h5ad,DOI: 10.1126/science.adf6812,,T,T,Source,other,abbreviations,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Middle temporal gyrus (MTG),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/015c230d-650c-4527-870d-8a805849a382.cxg/,https://datasets.cellxgene.cziscience.com/5f36898f-78e7-4ba0-950e-a02beca606d4.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Astro_4 Chandelier_1 Endo_1 L2/3 IT_1 L2/3 IT_2 L2/3 IT_3 L2/3 IT_4 L4 IT_1 L4 IT_2 L4 IT_3 L5 ET_1 L5 ET_2 L5 IT_1 L5 IT_2 L5/6 NP_1 L5/6 NP_2 L6 CT_1 L6 CT_2 L6 IT Car3_1 L6 IT_1 L6 IT_2 L6b_1 L6b_2 L6b_3 L6b_4 L6b_5 Lamp5 Lhx6_1 Lmpt5_1 Lmpt5_2 Lmpt5_3 Lmpt5_4 Lmpt5_5 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sst Chodl_1 Sst Chodl_2 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 VLMC_1 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Middle temporal gyrus (MTG),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/015c230d-650c-4527-870d-8a805849a382.cxg/,https://datasets.cellxgene.cziscience.com/5f36898f-78e7-4ba0-950e-a02beca606d4.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 ET L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary auditory cortex(A1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e2808a6e-e2ea-41b9-b38c-4a08f1677f02.cxg/,https://datasets.cellxgene.cziscience.com/4e2221b4-c204-4c28-bc6a-dcdb73c0d856.h5ad,DOI: 10.1126/science.adf6812,,T,T,Class,cell types,normal,excitatory inhibitory non-neuronal,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary auditory cortex(A1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e2808a6e-e2ea-41b9-b38c-4a08f1677f02.cxg/,https://datasets.cellxgene.cziscience.com/4e2221b4-c204-4c28-bc6a-dcdb73c0d856.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Astro_4 Astro_5 Chandelier_1 Endo_1 Endo_2 L2/3 IT_1 L2/3 IT_2 L2/3 IT_3 L2/3 IT_4 L2/3 IT_5 L2/3 IT_6 L4 IT_1 L4 IT_2 L4 IT_3 L4 IT_4 L4 IT_5 L5 ET_1 L5 ET_2 L5 ET_3 L5 ET_4 L5 IT_1 L5 IT_2 L5 IT_3 L5 IT_4 L5 IT_5 L5 IT_6 L5/6 NP_1 L5/6 NP_2 L5/6 NP_3 L5/6 NP_4 L5/6 NP_5 L5/6 NP_6 L6 CT_1 L6 CT_2 L6 CT_3 L6 IT Car3_1 L6 IT Car3_2 L6 IT_1 L6 IT_2 L6b_1 L6b_2 L6b_3 L6b_4 L6b_5 L6b_6 Lamp5 Lhx6_1 Lamp5_1 Lamp5_2 Lamp5_3 Lamp5_4 Lamp5_5 Lamp5_6 Lamp5_7 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Oligo_4 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sncg_8 Sst Chodl_1 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 Sst_33 Sst_34 Sst_35 Sst_36 Sst_37 VLMC_1 VLMC_2 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary auditory cortex(A1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e2808a6e-e2ea-41b9-b38c-4a08f1677f02.cxg/,https://datasets.cellxgene.cziscience.com/4e2221b4-c204-4c28-bc6a-dcdb73c0d856.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary auditory cortex(A1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e2808a6e-e2ea-41b9-b38c-4a08f1677f02.cxg/,https://datasets.cellxgene.cziscience.com/4e2221b4-c204-4c28-bc6a-dcdb73c0d856.h5ad,DOI: 10.1126/science.adf6812,,T,T,Layer,other,"abbreviations, normal",All L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary auditory cortex(A1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e2808a6e-e2ea-41b9-b38c-4a08f1677f02.cxg/,https://datasets.cellxgene.cziscience.com/4e2221b4-c204-4c28-bc6a-dcdb73c0d856.h5ad,DOI: 10.1126/science.adf6812,,T,T,Source,other,abbreviations,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary auditory cortex(A1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e2808a6e-e2ea-41b9-b38c-4a08f1677f02.cxg/,https://datasets.cellxgene.cziscience.com/4e2221b4-c204-4c28-bc6a-dcdb73c0d856.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Chandelier_1 Endo_1 L2/3 IT_1 L2/3 IT_2 L2/3 IT_3 L2/3 IT_4 L4 IT_1 L4 IT_2 L4 IT_3 L4 IT_4 L4 IT_5 L5 ET_1 L5 ET_2 L5 IT_1 L5 IT_2 L5 IT_3 L5 IT_4 L5/6 NP_1 L5/6 NP_2 L5/6 NP_3 L5/6 NP_4 L6 CT_1 L6 IT Car3_1 L6 IT Car3_2 L6 IT_1 L6 IT_2 L6 IT_3 L6 IT_4 L6b_1 L6b_2 L6b_3 L6b_4 Lamp5 Lhx6_1 Lamp5 Lhx6_2 Lmpt5_1 Lmpt5_2 Lmpt5_3 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_4 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sncg_8 Sst Chodl_1 Sst Chodl_2 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 Sst_33 Sst_34 Sst_35 Sst_36 Sst_37 Sst_38 VLMC_1 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary auditory cortex(A1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e2808a6e-e2ea-41b9-b38c-4a08f1677f02.cxg/,https://datasets.cellxgene.cziscience.com/4e2221b4-c204-4c28-bc6a-dcdb73c0d856.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 ET L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Anterior cingulate cortex (ACC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/be401db3-d732-408a-b0c4-71af0458b8ab.cxg/,https://datasets.cellxgene.cziscience.com/c662a5b4-2589-4829-965d-87f01f7b7c5f.h5ad,DOI: 10.1126/science.adf6812,,T,T,Class,cell types,normal,excitatory inhibitory non-neuronal,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Anterior cingulate cortex (ACC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/be401db3-d732-408a-b0c4-71af0458b8ab.cxg/,https://datasets.cellxgene.cziscience.com/c662a5b4-2589-4829-965d-87f01f7b7c5f.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Astro_4 Astro_5 Chandelier_1 Endo_1 Endo_2 L2/3 IT_1 L2/3 IT_2 L2/3 IT_3 L2/3 IT_4 L2/3 IT_5 L2/3 IT_6 L4 IT_1 L4 IT_2 L5 ET_1 L5 ET_2 L5 IT_1 L5 IT_2 L5 IT_3 L5 IT_4 L5 IT_5 L5 IT_6 L5/6 NP_1 L5/6 NP_2 L5/6 NP_3 L5/6 NP_4 L5/6 NP_5 L5/6 NP_6 L6 CT_1 L6 CT_2 L6 CT_3 L6 IT Car3_1 L6 IT Car3_2 L6 IT_1 L6 IT_2 L6b_1 L6b_2 L6b_3 L6b_4 L6b_5 L6b_6 Lamp5 Lhx6_1 Lamp5_1 Lamp5_2 Lamp5_3 Lamp5_4 Lamp5_5 Lamp5_6 Lamp5_7 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Oligo_4 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sncg_8 Sst Chodl_1 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 Sst_33 Sst_34 Sst_35 Sst_36 Sst_37 VLMC_1 VLMC_2 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Anterior cingulate cortex (ACC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/be401db3-d732-408a-b0c4-71af0458b8ab.cxg/,https://datasets.cellxgene.cziscience.com/c662a5b4-2589-4829-965d-87f01f7b7c5f.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 ET L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Anterior cingulate cortex (ACC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/be401db3-d732-408a-b0c4-71af0458b8ab.cxg/,https://datasets.cellxgene.cziscience.com/c662a5b4-2589-4829-965d-87f01f7b7c5f.h5ad,DOI: 10.1126/science.adf6812,,T,T,Layer,other,"abbreviations, normal",All L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Anterior cingulate cortex (ACC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/be401db3-d732-408a-b0c4-71af0458b8ab.cxg/,https://datasets.cellxgene.cziscience.com/c662a5b4-2589-4829-965d-87f01f7b7c5f.h5ad,DOI: 10.1126/science.adf6812,,T,T,Source,other,abbreviations,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Anterior cingulate cortex (ACC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/be401db3-d732-408a-b0c4-71af0458b8ab.cxg/,https://datasets.cellxgene.cziscience.com/c662a5b4-2589-4829-965d-87f01f7b7c5f.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Chandelier_1 Endo_1 L2/3 IT_1 L2/3 IT_2 L2/3 IT_3 L2/3 IT_4 L2/3 IT_5 L2/3 IT_6 L4 IT_1 L4 IT_2 L4 IT_3 L5 ET_1 L5 IT_1 L5 IT_2 L5 IT_3 L5 IT_4 L5 IT_5 L5/6 NP_1 L5/6 NP_2 L5/6 NP_3 L6 CT_1 L6 IT Car3_1 L6 IT_1 L6 IT_2 L6b_1 L6b_2 L6b_3 L6b_4 Lamp5 Lhx6_1 Lmpt5_1 Lmpt5_2 Lmpt5_3 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sncg_8 Sncg_9 Sst Chodl_1 Sst Chodl_2 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 Sst_33 Sst_34 Sst_35 VLMC_1 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Anterior cingulate cortex (ACC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/be401db3-d732-408a-b0c4-71af0458b8ab.cxg/,https://datasets.cellxgene.cziscience.com/c662a5b4-2589-4829-965d-87f01f7b7c5f.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 ET L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: CGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e4ddac12-f48f-4455-8e8d-c2a48a683437.cxg/,https://datasets.cellxgene.cziscience.com/cf59a3de-b569-4b4c-aa4c-ff30c4f5fd90.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_cluster,cell types,abbreviations,Lamp5 Lhx6_1 Lamp5_1 Lamp5_2 Lamp5_3 Lamp5_4 Lamp5_5 Lamp5_6 Lamp5_7 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sncg_8 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: CGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e4ddac12-f48f-4455-8e8d-c2a48a683437.cxg/,https://datasets.cellxgene.cziscience.com/cf59a3de-b569-4b4c-aa4c-ff30c4f5fd90.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_subclass,cell types,abbreviations,Lamp5 Lamp5 Lhx6 Pax6 Sncg Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: CGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e4ddac12-f48f-4455-8e8d-c2a48a683437.cxg/,https://datasets.cellxgene.cziscience.com/cf59a3de-b569-4b4c-aa4c-ff30c4f5fd90.h5ad,DOI: 10.1126/science.adf6812,,T,T,Layer,other,"abbreviations, normal",All L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: CGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e4ddac12-f48f-4455-8e8d-c2a48a683437.cxg/,https://datasets.cellxgene.cziscience.com/cf59a3de-b569-4b4c-aa4c-ff30c4f5fd90.h5ad,DOI: 10.1126/science.adf6812,,T,T,Location,other,normal,caudal lateral caudal medial central lateral central lateral central medial rostral medial rostral middle,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: CGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e4ddac12-f48f-4455-8e8d-c2a48a683437.cxg/,https://datasets.cellxgene.cziscience.com/cf59a3de-b569-4b4c-aa4c-ff30c4f5fd90.h5ad,DOI: 10.1126/science.adf6812,,T,T,Region,other,abbreviations,A1 ACC ANG DLPFC M1 MTG S1 V1,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: CGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e4ddac12-f48f-4455-8e8d-c2a48a683437.cxg/,https://datasets.cellxgene.cziscience.com/cf59a3de-b569-4b4c-aa4c-ff30c4f5fd90.h5ad,DOI: 10.1126/science.adf6812,,T,T,Source,other,abbreviations,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: CGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e4ddac12-f48f-4455-8e8d-c2a48a683437.cxg/,https://datasets.cellxgene.cziscience.com/cf59a3de-b569-4b4c-aa4c-ff30c4f5fd90.h5ad,DOI: 10.1126/science.adf6812,,T,T,Subregion,other,abbreviations,A1C ACC ANG DLPFC M1C MTG S1C V1C V1C_L5 V1_L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: CGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e4ddac12-f48f-4455-8e8d-c2a48a683437.cxg/,https://datasets.cellxgene.cziscience.com/cf59a3de-b569-4b4c-aa4c-ff30c4f5fd90.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,abbreviations,Lamp5 Lhx6_1 Lamp5 Lhx6_2 Lamp5_1 Lamp5_2 Lamp5_3 Lamp5_4 Lamp5_5 Lamp5_6 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pax6_5 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sncg_8 Sncg_9 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29 Vip_30 Vip_31,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: CGE-derived interneurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/e4ddac12-f48f-4455-8e8d-c2a48a683437.cxg/,https://datasets.cellxgene.cziscience.com/cf59a3de-b569-4b4c-aa4c-ff30c4f5fd90.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,abbreviation,Lamp5 Lamp5 Lhx6 Pax6 Sncg Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary motor cortex (M1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5bdc423a-59e6-457d-aa01-debd2c9c564f.cxg/,https://datasets.cellxgene.cziscience.com/0b3d19b3-df06-4265-9803-82f598e59dba.h5ad,DOI: 10.1126/science.adf6812,,T,T,Class,cell types,abbreviations,excitatory inhibitory non-neuronal,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary motor cortex (M1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5bdc423a-59e6-457d-aa01-debd2c9c564f.cxg/,https://datasets.cellxgene.cziscience.com/0b3d19b3-df06-4265-9803-82f598e59dba.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Astro_4 Astro_5 Chandelier_1 Endo_2 L2/3 IT_1 L2/3 IT_2 L2/3 IT_3 L2/3 IT_4 L2/3 IT_5 L2/3 IT_6 L4 IT_1 L4 IT_5 L5 ET_1 L5 ET_2 L5 IT_1 L5 IT_2 L5 IT_3 L5 IT_6 L5/6 NP_1 L5/6 NP_2 L5/6 NP_3 L5/6 NP_5 L5/6 NP_6 L6 CT_1 L6 CT_2 L6 CT_3 L6 IT Car3_1 L6 IT Car3_2 L6 IT_1 L6 IT_2 L6 IT_3 L6 IT_4 L6 IT_5 L6 IT_6 Lamp5 Lhx6_1 Lamp5_1 Lamp5_2 Lamp5_3 Lamp5_4 Lamp5_5 Lamp5_6 Lamp5_7 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Oligo_4 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sncg_8 Sst Chodl_1 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 Sst_33 Sst_34 Sst_35 Sst_36 Sst_37 VLMC_1 VLMC_2 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary motor cortex (M1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5bdc423a-59e6-457d-aa01-debd2c9c564f.cxg/,https://datasets.cellxgene.cziscience.com/0b3d19b3-df06-4265-9803-82f598e59dba.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 ET L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary motor cortex (M1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5bdc423a-59e6-457d-aa01-debd2c9c564f.cxg/,https://datasets.cellxgene.cziscience.com/0b3d19b3-df06-4265-9803-82f598e59dba.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Chandelier_1 Endo_1 L2/3 IT_1 L2/3 IT_2 L2/3 IT_3 L2/3 IT_4 L2/3 IT_5 L4 IT_1 L4 IT_2 L4 IT_3 L5 ET_1 L5 ET_2 L5 ET_3 L5 IT_1 L5 IT_2 L5 IT_3 L5 IT_4 L5/6 NP_1 L5/6 NP_2 L5/6 NP_3 L5/6 NP_4 L6 CT_1 L6 CT_2 L6 CT_3 L6 CT_4 L6 IT Car3_1 L6 IT_1 L6 IT_2 L6b_1 L6b_2 L6b_3 L6b_4 L6b_5 L6b_6 Lamp5 Lhx6_1 Lamp5 Lhx6_2 Lamp_1 Lmpt5_2 Lmpt5_3 Lmpt5_4 Lmpt5_5 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pax6_5 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Pvalb_10 Pvalb_11 Pvalb_12 Pvalb_13 Pvalb_14 Pvalb_15 Pvalb_16 Pvalb_17 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sst Chodl_1 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 VLMC_1 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29 Vip_30 Vip_31,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Primary motor cortex (M1),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5bdc423a-59e6-457d-aa01-debd2c9c564f.cxg/,https://datasets.cellxgene.cziscience.com/0b3d19b3-df06-4265-9803-82f598e59dba.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 ET L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Dorsolateral prefrontal cortex (DFC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/716a4acc-919e-4326-9672-ebe06ede84e6.cxg/,https://datasets.cellxgene.cziscience.com/a2e7b6e9-79d5-446d-8fb1-19128c97a48f.h5ad,DOI: 10.1126/science.adf6812,,T,T,Class,cell types,normal,excitatory inhibitory non-neuronal,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Dorsolateral prefrontal cortex (DFC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/716a4acc-919e-4326-9672-ebe06ede84e6.cxg/,https://datasets.cellxgene.cziscience.com/a2e7b6e9-79d5-446d-8fb1-19128c97a48f.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Astro_4 Astro_5 Chandelier_1 Endo_1 Endo_2 L2/3 IT_1 L2/3 IT_2 L2/3 IT_3 L2/3 IT_4 L2/3 IT_5 L2/3 IT_6 L4 IT_1 L4 IT_2 L4 IT_3 L4 IT_4 L4 IT_5 L4 IT_6 L5 ET_1 L5 ET_2 L5 IT_1 L5 IT_2 L5 IT_3 L5 IT_4 L5 IT_5 L5 IT_6 L5/6 NP_1 L5/6 NP_2 L5/6 NP_3 L5/6 NP_5 L5/6 NP_6 L6 CT_2 L6 CT_3 L6 IT Car3_2 L6 IT_1 L6 IT_2 Lb6_1 Lb6_2 Lb6_3 Lb6_4 Lb6_5 Lb6_6 Lamp5 Lhx6_1 Lamp5_1 Lamp5_2 Lamp5_3 Lamp5_4 Lamp5_5 Lamp5_6 Lamp5_7 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Oligo_4 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sncg_8 Sst Chodl_1 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 Sst_33 Sst_34 Sst_35 Sst_36 Sst_37 VLMC_1 VLMC_2 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Dorsolateral prefrontal cortex (DFC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/716a4acc-919e-4326-9672-ebe06ede84e6.cxg/,https://datasets.cellxgene.cziscience.com/a2e7b6e9-79d5-446d-8fb1-19128c97a48f.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 ET L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Dorsolateral prefrontal cortex (DFC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/716a4acc-919e-4326-9672-ebe06ede84e6.cxg/,https://datasets.cellxgene.cziscience.com/a2e7b6e9-79d5-446d-8fb1-19128c97a48f.h5ad,DOI: 10.1126/science.adf6812,,T,T,Layer,other,"abbreviations, normal",All L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Dorsolateral prefrontal cortex (DFC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/716a4acc-919e-4326-9672-ebe06ede84e6.cxg/,https://datasets.cellxgene.cziscience.com/a2e7b6e9-79d5-446d-8fb1-19128c97a48f.h5ad,DOI: 10.1126/science.adf6812,,T,T,Source,other,abbreviation,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Dorsolateral prefrontal cortex (DFC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/716a4acc-919e-4326-9672-ebe06ede84e6.cxg/,https://datasets.cellxgene.cziscience.com/a2e7b6e9-79d5-446d-8fb1-19128c97a48f.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Chandelier_1 Endo_1 L2/3 IT_1 L2/3 IT_2 L2/3 IT_3 L2/3 IT_4 L4 IT_1 L4 IT_2 L5 ET_1 L5 ET_2 L5 IT_1 L5 IT_2 L5 IT_3 L5/6 NP_1 L5/6 NP_2 L5/6 NP_3 L6 CT_1 L6 IT Car3_1 L6 IT_1 L6 IT_2 L6 IT_3 L6 IT_4 Lamp5 Lhx6_1 Lamp5 Lhx6_2 Lamp_1 Lmpt5_2 Lmpt5_3 Lmpt5_4 Lmpt5_5 Lmpt5_6 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Oligo_4 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sncg_8 Sst Chodl_1 Sst Chodl_2 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 VLMC_1 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Dorsolateral prefrontal cortex (DFC),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/716a4acc-919e-4326-9672-ebe06ede84e6.cxg/,https://datasets.cellxgene.cziscience.com/a2e7b6e9-79d5-446d-8fb1-19128c97a48f.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 ET L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Angular gyrus (AnG),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/f5b0810c-1664-4a62-ad06-be1d9964aa8b.cxg/,https://datasets.cellxgene.cziscience.com/01afd5b8-21be-4869-a686-1fe94ff6f4d8.h5ad,DOI: 10.1126/science.adf6812,,T,T,Class,cell types,normal,excitatory inhibitory non-neuronal,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Angular gyrus (AnG),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/f5b0810c-1664-4a62-ad06-be1d9964aa8b.cxg/,https://datasets.cellxgene.cziscience.com/01afd5b8-21be-4869-a686-1fe94ff6f4d8.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_cluster,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 ET L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Angular gyrus (AnG),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/f5b0810c-1664-4a62-ad06-be1d9964aa8b.cxg/,https://datasets.cellxgene.cziscience.com/01afd5b8-21be-4869-a686-1fe94ff6f4d8.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 ET L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Angular gyrus (AnG),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/f5b0810c-1664-4a62-ad06-be1d9964aa8b.cxg/,https://datasets.cellxgene.cziscience.com/01afd5b8-21be-4869-a686-1fe94ff6f4d8.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,"abbreviations, normal",Astro_1 Astro_2 Astro_3 Astro_4 Astro_5 Chandelier_1 Endo_1 Endo_2 L2/3 IT_1 L2/3 IT_2 L2/3 IT_4 L2/3 IT_5 L2/3 IT_6 L4 IT_1 L4 IT_5 L5 ET_1 L5 ET_2 L5 ET_3 L5 IT_1 L5 IT_2 L5 IT_3 L5 IT_4 L5 IT_5 L5 IT_6 L5/6 NP_1 L5/6 NP_3 L5/6 NP_4 L5/6 NP_5 L6 CT_1 L6 CT_3 L6 IT Car3_1 L6 IT Car3_2 L6 IT_1 L6 IT_2 Lb6_1 Lb6_2 Lb6_3 Lb6_4 Lb6_5 Lb6_6 Lamp5 Lhx6_1 Lamp5_1 Lamp5_2 Lamp5_3 Lamp5_4 Lamp5_5 Lamp5_6 Lamp5_7 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Oligo_4 Pax6_1 Pax6_2 Pax6_3 Pax6_4 Pvalb_1 Pvalb_2 Pvalb_3 Pvalb_4 Pvalb_5 Pvalb_6 Pvalb_7 Pvalb_8 Pvalb_9 Sncg_1 Sncg_2 Sncg_3 Sncg_4 Sncg_5 Sncg_6 Sncg_7 Sncg_8 Sst Chodl_1 Sst_1 Sst_2 Sst_3 Sst_4 Sst_5 Sst_6 Sst_7 Sst_8 Sst_9 Sst_10 Sst_11 Sst_12 Sst_13 Sst_14 Sst_15 Sst_16 Sst_17 Sst_18 Sst_19 Sst_20 Sst_21 Sst_22 Sst_23 Sst_24 Sst_25 Sst_26 Sst_27 Sst_28 Sst_29 Sst_30 Sst_31 Sst_32 Sst_33 Sst_34 Sst_35 Sst_36 Sst_37 VLMC_1 VLMC_2 Vip_1 Vip_2 Vip_3 Vip_4 Vip_5 Vip_6 Vip_7 Vip_8 Vip_9 Vip_10 Vip_11 Vip_12 Vip_13 Vip_14 Vip_15 Vip_16 Vip_17 Vip_18 Vip_19 Vip_20 Vip_21 Vip_22 Vip_23 Vip_24 Vip_25 Vip_26 Vip_27 Vip_28 Vip_29,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Dissection: Angular gyrus (AnG),Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/f5b0810c-1664-4a62-ad06-be1d9964aa8b.cxg/,https://datasets.cellxgene.cziscience.com/01afd5b8-21be-4869-a686-1fe94ff6f4d8.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,"abbreviations, normal",Astro Chandelier Endo L2/3 IT L4 IT L5 ET L5 IT L5/6 NP L6 CT L6 IT L6 IT Car3 L6b Lamp5 Lamp5 Lhx6 Micro/PVM OPC Oligo Pax6 Pvalb Sncg Sst Sst Chodl VLMC Vip,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Non-neuronal cells,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5346f9c6-755e-4336-94cc-38706ec00c2f.cxg/,https://datasets.cellxgene.cziscience.com/4df5ea20-265e-4cec-b09a-e590193576c2.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_cluster,cell types,abbreviations,Astro_1 Astro_2 Astro_3 Astro_4 Astro_5 Endo_1 Endo_2 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Oligo_4 VLMC_1 VLMC_2,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Non-neuronal cells,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5346f9c6-755e-4336-94cc-38706ec00c2f.cxg/,https://datasets.cellxgene.cziscience.com/4df5ea20-265e-4cec-b09a-e590193576c2.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_subclass,cell types,abbreviations,Astro Endo Micro/PVM OPC Oligo VLMC,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Non-neuronal cells,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5346f9c6-755e-4336-94cc-38706ec00c2f.cxg/,https://datasets.cellxgene.cziscience.com/4df5ea20-265e-4cec-b09a-e590193576c2.h5ad,DOI: 10.1126/science.adf6812,,T,T,Layer,other,"abbreviations, normal",All L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Non-neuronal cells,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5346f9c6-755e-4336-94cc-38706ec00c2f.cxg/,https://datasets.cellxgene.cziscience.com/4df5ea20-265e-4cec-b09a-e590193576c2.h5ad,DOI: 10.1126/science.adf6812,,T,T,Location,other,normal,caudal lateral caudal medial central lateral central lateral central medial rostral medial rostral middle,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Non-neuronal cells,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5346f9c6-755e-4336-94cc-38706ec00c2f.cxg/,https://datasets.cellxgene.cziscience.com/4df5ea20-265e-4cec-b09a-e590193576c2.h5ad,DOI: 10.1126/science.adf6812,,T,T,Region,other,abbreviations,A1 ACC ANG DLPFC M1 MTG S1 V1,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Non-neuronal cells,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5346f9c6-755e-4336-94cc-38706ec00c2f.cxg/,https://datasets.cellxgene.cziscience.com/4df5ea20-265e-4cec-b09a-e590193576c2.h5ad,DOI: 10.1126/science.adf6812,,T,T,Source,other,abbreviations,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Non-neuronal cells,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5346f9c6-755e-4336-94cc-38706ec00c2f.cxg/,https://datasets.cellxgene.cziscience.com/4df5ea20-265e-4cec-b09a-e590193576c2.h5ad,DOI: 10.1126/science.adf6812,,T,T,Subregion,other,abbreviations,A1C ACC ANG DLPFC M1C MTG S1C V1C V1C_L5 V1_L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Non-neuronal cells,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5346f9c6-755e-4336-94cc-38706ec00c2f.cxg/,https://datasets.cellxgene.cziscience.com/4df5ea20-265e-4cec-b09a-e590193576c2.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,abbreviations,Astro_1 Astro_2 Astro_3 Astro_4 Astro_5 Endo_1 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Oligo_4 VLMC_1 VLMC_2 Micro/PVM_1 OPC_1 Oligo_1 Oligo_2 Oligo_3 Oligo_4 VLMC_1 VLMC_2,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Non-neuronal cells,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/5346f9c6-755e-4336-94cc-38706ec00c2f.cxg/,https://datasets.cellxgene.cziscience.com/4df5ea20-265e-4cec-b09a-e590193576c2.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,abbreviations,Astro Endo Micro/PVM OPC Oligo VLMC,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Deep layer (non-IT) excitatory neurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/d01c9dff-abd1-4825-bf30-2eb2ba74597e.cxg/,https://datasets.cellxgene.cziscience.com/839cae6e-36e9-4aad-a0fd-99ffe8897c56.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_cluster,cell types,abbreviations,L5 ET_1 L5 ET_2 L5 ET_3 L5 ET_4 L5/6 NP_1 L5/6 NP_2 L5/6 NP_3 L5/6 NP_4 L5/6 NP_5 L5/6 NP_6 L6 CT_1 L6 CT_2 L6 CT_3 L6b_1 L6b_2 L6b_3 L6b_4 L6b_5 L6b_6,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Deep layer (non-IT) excitatory neurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/d01c9dff-abd1-4825-bf30-2eb2ba74597e.cxg/,https://datasets.cellxgene.cziscience.com/839cae6e-36e9-4aad-a0fd-99ffe8897c56.h5ad,DOI: 10.1126/science.adf6812,,T,T,CrossArea_subclass,cell types,abbreviations,L5 ET L5/6 NP L6 CT L6b,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Deep layer (non-IT) excitatory neurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/d01c9dff-abd1-4825-bf30-2eb2ba74597e.cxg/,https://datasets.cellxgene.cziscience.com/839cae6e-36e9-4aad-a0fd-99ffe8897c56.h5ad,DOI: 10.1126/science.adf6812,,T,T,Layer,other,"abbreviations, normal",All L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Deep layer (non-IT) excitatory neurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/d01c9dff-abd1-4825-bf30-2eb2ba74597e.cxg/,https://datasets.cellxgene.cziscience.com/839cae6e-36e9-4aad-a0fd-99ffe8897c56.h5ad,DOI: 10.1126/science.adf6812,,T,T,Location,other,normal,caudal lateral caudal medial central lateral central lateral central medial rostral medial rostral middle,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Deep layer (non-IT) excitatory neurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/d01c9dff-abd1-4825-bf30-2eb2ba74597e.cxg/,https://datasets.cellxgene.cziscience.com/839cae6e-36e9-4aad-a0fd-99ffe8897c56.h5ad,DOI: 10.1126/science.adf6812,,T,T,Region,other,abbreviations,A1 ACC ANG DLPFC M1 MTG S1 V1,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Deep layer (non-IT) excitatory neurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/d01c9dff-abd1-4825-bf30-2eb2ba74597e.cxg/,https://datasets.cellxgene.cziscience.com/839cae6e-36e9-4aad-a0fd-99ffe8897c56.h5ad,DOI: 10.1126/science.adf6812,,T,T,Source,other,abbreviations,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Deep layer (non-IT) excitatory neurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/d01c9dff-abd1-4825-bf30-2eb2ba74597e.cxg/,https://datasets.cellxgene.cziscience.com/839cae6e-36e9-4aad-a0fd-99ffe8897c56.h5ad,DOI: 10.1126/science.adf6812,,T,T,Subregion,other,abbreviations,A1C ACC ANG DLPFC M1C MTG S1C V1C V1C_L5 V1_L5,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Deep layer (non-IT) excitatory neurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/d01c9dff-abd1-4825-bf30-2eb2ba74597e.cxg/,https://datasets.cellxgene.cziscience.com/839cae6e-36e9-4aad-a0fd-99ffe8897c56.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_cluster,cell types,abbreviations,L5 ET_1 L5 ET_2 L5 ET_3 L5/6 NP_1 L5/6 NP_2 L5/6 NP_3 L5/6 NP_4 L5/6 NP_5 L6 CT_1 L6 CT_2 L6 CT_3 L6 CT_4 L6b_1 L6b_2 L6b_3 L6b_4 L6b_5 L6b_6,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Supercluster: Deep layer (non-IT) excitatory neurons,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/d01c9dff-abd1-4825-bf30-2eb2ba74597e.cxg/,https://datasets.cellxgene.cziscience.com/839cae6e-36e9-4aad-a0fd-99ffe8897c56.h5ad,DOI: 10.1126/science.adf6812,,T,T,WithinArea_subclass,cell types,abbreviations,L5 ET L5/6 NP L6 CT L6b,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,Specimen ID,other,abbreviation,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,Tissue (RIN),other,abbreviation,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,cause_of_death,other,normal,cardiovascular disease mitral valve prolapse,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,cell_type_accession,other,abbreviation,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,cell_type_alias,cell types,abbreviation,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,cell_type_alt_alias,cell types,"abbreviaiton, normal",,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,cell_type_designation,other,normal,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,class,cell types,normal,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,cluster,cell types,abbreviations,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,cortical_layer,other,abbreviations,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,outlier_call,other,X,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,outlier_type,other,X,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,region,other,abbreviation,,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +Human Multiple Cortical Areas SMART-seq,Transcriptomic cytoarchitecture reveals principles of human neocortex organization,https://cellxgene.cziscience.com/e/a5d5c529-8a1f-40b5-bda3-35208970070d.cxg/,https://datasets.cellxgene.cziscience.com/77a91ab6-4fcc-428d-b719-a3f1238df262.h5ad,DOI: 10.1126/science.adf6812,,T,T,subclass,cell types,"abbreviation, normal",,Jorstad et al. (2023) Science,https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f,Normal,Adult +white matter - all cells,"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function",https://cellxgene.cziscience.com/e/c05e6940-729c-47bd-a2a6-6ce3730c4919.cxg/,https://datasets.cellxgene.cziscience.com/79772e00-00d5-497e-b8ff-f83af5ce59c1.h5ad,https://doi.org/10.1186/s40478-023-01568-z,,T,T,10XBatch,other,abbreviations,,Seeker et al. (2023) acta neuropathol commun,https://cellxgene.cziscience.com/collections/9d63fcf1-5ca0-4006-8d8f-872f3327dbe9,Normal,Adult +white matter - all cells,"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function",https://cellxgene.cziscience.com/e/c05e6940-729c-47bd-a2a6-6ce3730c4919.cxg/,https://datasets.cellxgene.cziscience.com/79772e00-00d5-497e-b8ff-f83af5ce59c1.h5ad,https://doi.org/10.1186/s40478-023-01568-z,,T,T,AgeGroup,other,abbreviations,,Seeker et al. (2023) acta neuropathol commun,https://cellxgene.cziscience.com/collections/9d63fcf1-5ca0-4006-8d8f-872f3327dbe9,Normal,Adult +white matter - all cells,"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function",https://cellxgene.cziscience.com/e/c05e6940-729c-47bd-a2a6-6ce3730c4919.cxg/,https://datasets.cellxgene.cziscience.com/79772e00-00d5-497e-b8ff-f83af5ce59c1.h5ad,https://doi.org/10.1186/s40478-023-01568-z,,T,T,CauseOfDeath_category,other,abbreviations,,Seeker et al. (2023) acta neuropathol commun,https://cellxgene.cziscience.com/collections/9d63fcf1-5ca0-4006-8d8f-872f3327dbe9,Normal,Adult +white matter - all cells,"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function",https://cellxgene.cziscience.com/e/c05e6940-729c-47bd-a2a6-6ce3730c4919.cxg/,https://datasets.cellxgene.cziscience.com/79772e00-00d5-497e-b8ff-f83af5ce59c1.h5ad,https://doi.org/10.1186/s40478-023-01568-z,,T,T,ID,other,abbreviations,,Seeker et al. (2023) acta neuropathol commun,https://cellxgene.cziscience.com/collections/9d63fcf1-5ca0-4006-8d8f-872f3327dbe9,Normal,Adult +white matter - all cells,"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function",https://cellxgene.cziscience.com/e/c05e6940-729c-47bd-a2a6-6ce3730c4919.cxg/,https://datasets.cellxgene.cziscience.com/79772e00-00d5-497e-b8ff-f83af5ce59c1.h5ad,https://doi.org/10.1186/s40478-023-01568-z,,T,T,SequencingPool,other,abbreviations,,Seeker et al. (2023) acta neuropathol commun,https://cellxgene.cziscience.com/collections/9d63fcf1-5ca0-4006-8d8f-872f3327dbe9,Normal,Adult +white matter - all cells,"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function",https://cellxgene.cziscience.com/e/c05e6940-729c-47bd-a2a6-6ce3730c4919.cxg/,https://datasets.cellxgene.cziscience.com/79772e00-00d5-497e-b8ff-f83af5ce59c1.h5ad,https://doi.org/10.1186/s40478-023-01568-z,,T,T,author_cell_type,cell types,abbreviations,,Seeker et al. (2023) acta neuropathol commun,https://cellxgene.cziscience.com/collections/9d63fcf1-5ca0-4006-8d8f-872f3327dbe9,Normal,Adult +white matter - all cells,"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function",https://cellxgene.cziscience.com/e/c05e6940-729c-47bd-a2a6-6ce3730c4919.cxg/,https://datasets.cellxgene.cziscience.com/79772e00-00d5-497e-b8ff-f83af5ce59c1.h5ad,https://doi.org/10.1186/s40478-023-01568-z,,T,T,broad_cell_type,cell types,normal,,Seeker et al. (2023) acta neuropathol commun,https://cellxgene.cziscience.com/collections/9d63fcf1-5ca0-4006-8d8f-872f3327dbe9,Normal,Adult +white matter - all cells,"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function",https://cellxgene.cziscience.com/e/c05e6940-729c-47bd-a2a6-6ce3730c4919.cxg/,https://datasets.cellxgene.cziscience.com/79772e00-00d5-497e-b8ff-f83af5ce59c1.h5ad,https://doi.org/10.1186/s40478-023-01568-z,,T,T,donor_cause_of_death,other,abbreviations,,Seeker et al. (2023) acta neuropathol commun,https://cellxgene.cziscience.com/collections/9d63fcf1-5ca0-4006-8d8f-872f3327dbe9,Normal,Adult +white matter - all cells,"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function",https://cellxgene.cziscience.com/e/c05e6940-729c-47bd-a2a6-6ce3730c4919.cxg/,https://datasets.cellxgene.cziscience.com/79772e00-00d5-497e-b8ff-f83af5ce59c1.h5ad,https://doi.org/10.1186/s40478-023-01568-z,,T,T,library_uuid,other,abbreviations,,Seeker et al. (2023) acta neuropathol commun,https://cellxgene.cziscience.com/collections/9d63fcf1-5ca0-4006-8d8f-872f3327dbe9,Normal,Adult +white matter - all cells,"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function",https://cellxgene.cziscience.com/e/c05e6940-729c-47bd-a2a6-6ce3730c4919.cxg/,https://datasets.cellxgene.cziscience.com/79772e00-00d5-497e-b8ff-f83af5ce59c1.h5ad,https://doi.org/10.1186/s40478-023-01568-z,,T,T,sample_uuid,other,abbreviations,,Seeker et al. (2023) acta neuropathol commun,https://cellxgene.cziscience.com/collections/9d63fcf1-5ca0-4006-8d8f-872f3327dbe9,Normal,Adult +white matter - all cells,"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function",https://cellxgene.cziscience.com/e/c05e6940-729c-47bd-a2a6-6ce3730c4919.cxg/,https://datasets.cellxgene.cziscience.com/79772e00-00d5-497e-b8ff-f83af5ce59c1.h5ad,https://doi.org/10.1186/s40478-023-01568-z,,T,T,suspension_uuid,other,abbreviations,,Seeker et al. (2023) acta neuropathol commun,https://cellxgene.cziscience.com/collections/9d63fcf1-5ca0-4006-8d8f-872f3327dbe9,Normal,Adult +white matter - all cells,"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function",https://cellxgene.cziscience.com/e/c05e6940-729c-47bd-a2a6-6ce3730c4919.cxg/,https://datasets.cellxgene.cziscience.com/79772e00-00d5-497e-b8ff-f83af5ce59c1.h5ad,https://doi.org/10.1186/s40478-023-01568-z,,T,T,tissue_handling_interval,other,abbreviations,,Seeker et al. (2023) acta neuropathol commun,https://cellxgene.cziscience.com/collections/9d63fcf1-5ca0-4006-8d8f-872f3327dbe9,Normal,Adult +"Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse","Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse",https://cellxgene.cziscience.com/e/9b686bb6-1427-4e13-b451-7ee961115cf9.cxg/,https://datasets.cellxgene.cziscience.com/1af9835f-469e-452f-a91d-f42af3f91042.h5ad,https://doi.org/10.1038/s41586-021-03465-8,,T,T,BICCN_cluster_label,cell types,abbreviations,,Bakken et al. (2021) Nature,https://cellxgene.cziscience.com/collections/367d95c0-0eb0-4dae-8276-9407239421ee,Normal,Adult +"Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse","Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse",https://cellxgene.cziscience.com/e/9b686bb6-1427-4e13-b451-7ee961115cf9.cxg/,https://datasets.cellxgene.cziscience.com/1af9835f-469e-452f-a91d-f42af3f91042.h5ad,https://doi.org/10.1038/s41586-021-03465-8,,T,T,BICCN_subclass_label,cell types,abbreviations,,Bakken et al. (2021) Nature,https://cellxgene.cziscience.com/collections/367d95c0-0eb0-4dae-8276-9407239421ee,Normal,Adult +"Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse","Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse",https://cellxgene.cziscience.com/e/9b686bb6-1427-4e13-b451-7ee961115cf9.cxg/,https://datasets.cellxgene.cziscience.com/1af9835f-469e-452f-a91d-f42af3f91042.h5ad,https://doi.org/10.1038/s41586-021-03465-8,,T,T,cluster_color,other,abbreviations,,Bakken et al. (2021) Nature,https://cellxgene.cziscience.com/collections/367d95c0-0eb0-4dae-8276-9407239421ee,Normal,Adult +"Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse","Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse",https://cellxgene.cziscience.com/e/9b686bb6-1427-4e13-b451-7ee961115cf9.cxg/,https://datasets.cellxgene.cziscience.com/1af9835f-469e-452f-a91d-f42af3f91042.h5ad,https://doi.org/10.1038/s41586-021-03465-8,,T,T,integrated_snn_res.6,other,abbreviations,,Bakken et al. (2021) Nature,https://cellxgene.cziscience.com/collections/367d95c0-0eb0-4dae-8276-9407239421ee,Normal,Adult +"Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse","Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse",https://cellxgene.cziscience.com/e/9b686bb6-1427-4e13-b451-7ee961115cf9.cxg/,https://datasets.cellxgene.cziscience.com/1af9835f-469e-452f-a91d-f42af3f91042.h5ad,https://doi.org/10.1038/s41586-021-03465-8,,T,T,label_for_heatmap,cell types,abbreviations,,Bakken et al. (2021) Nature,https://cellxgene.cziscience.com/collections/367d95c0-0eb0-4dae-8276-9407239421ee,Normal,Adult +"Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse","Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse",https://cellxgene.cziscience.com/e/9b686bb6-1427-4e13-b451-7ee961115cf9.cxg/,https://datasets.cellxgene.cziscience.com/1af9835f-469e-452f-a91d-f42af3f91042.h5ad,https://doi.org/10.1038/s41586-021-03465-8,,T,T,sample_id,other,abbreviations,,Bakken et al. (2021) Nature,https://cellxgene.cziscience.com/collections/367d95c0-0eb0-4dae-8276-9407239421ee,Normal,Adult +"Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse","Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse",https://cellxgene.cziscience.com/e/9b686bb6-1427-4e13-b451-7ee961115cf9.cxg/,https://datasets.cellxgene.cziscience.com/1af9835f-469e-452f-a91d-f42af3f91042.h5ad,https://doi.org/10.1038/s41586-021-03465-8,,T,T,seurat_clusters,other,abbreviations,,Bakken et al. (2021) Nature,https://cellxgene.cziscience.com/collections/367d95c0-0eb0-4dae-8276-9407239421ee,Normal,Adult +snRNA-seq of human anterior and posterior hippocampus,Resolving cellular and molecular diversity along the hippocampal anterior-to-posterior axis in humans,https://cellxgene.cziscience.com/e/94c41723-b2c4-4b59-a49a-64c9b851903e.cxg/,https://datasets.cellxgene.cziscience.com/3f096be5-dedf-4f7b-a8ed-8d309d18bbde.h5ad,https://doi.org/10.1016/j.neuron.2021.05.003,,T,T,author_cell_type,cell types,abbreviations,,Ayhan et al. (2021) Neuron,https://cellxgene.cziscience.com/collections/f17b9205-f61f-4a0f-a65a-73ba91c50ade,Normal,Adult +snRNA-seq of human anterior and posterior hippocampus,Resolving cellular and molecular diversity along the hippocampal anterior-to-posterior axis in humans,https://cellxgene.cziscience.com/e/94c41723-b2c4-4b59-a49a-64c9b851903e.cxg/,https://datasets.cellxgene.cziscience.com/3f096be5-dedf-4f7b-a8ed-8d309d18bbde.h5ad,https://doi.org/10.1016/j.neuron.2021.05.003,,T,T,batch,other,abbreviations,,Ayhan et al. (2021) Neuron,https://cellxgene.cziscience.com/collections/f17b9205-f61f-4a0f-a65a-73ba91c50ade,Normal,Adult +snRNA-seq of human anterior and posterior hippocampus,Resolving cellular and molecular diversity along the hippocampal anterior-to-posterior axis in humans,https://cellxgene.cziscience.com/e/94c41723-b2c4-4b59-a49a-64c9b851903e.cxg/,https://datasets.cellxgene.cziscience.com/3f096be5-dedf-4f7b-a8ed-8d309d18bbde.h5ad,https://doi.org/10.1016/j.neuron.2021.05.003,,T,T,group,other,abbreviations,,Ayhan et al. (2021) Neuron,https://cellxgene.cziscience.com/collections/f17b9205-f61f-4a0f-a65a-73ba91c50ade,Normal,Adult +snRNA-seq of human anterior and posterior hippocampus,Resolving cellular and molecular diversity along the hippocampal anterior-to-posterior axis in humans,https://cellxgene.cziscience.com/e/94c41723-b2c4-4b59-a49a-64c9b851903e.cxg/,https://datasets.cellxgene.cziscience.com/3f096be5-dedf-4f7b-a8ed-8d309d18bbde.h5ad,https://doi.org/10.1016/j.neuron.2021.05.003,,T,T,hemisphere,other,abbreviations,,Ayhan et al. (2021) Neuron,https://cellxgene.cziscience.com/collections/f17b9205-f61f-4a0f-a65a-73ba91c50ade,Normal,Adult +snRNA-seq of human anterior and posterior hippocampus,Resolving cellular and molecular diversity along the hippocampal anterior-to-posterior axis in humans,https://cellxgene.cziscience.com/e/94c41723-b2c4-4b59-a49a-64c9b851903e.cxg/,https://datasets.cellxgene.cziscience.com/3f096be5-dedf-4f7b-a8ed-8d309d18bbde.h5ad,https://doi.org/10.1016/j.neuron.2021.05.003,,T,T,orig.ident,other,abbreviations,,Ayhan et al. (2021) Neuron,https://cellxgene.cziscience.com/collections/f17b9205-f61f-4a0f-a65a-73ba91c50ade,Normal,Adult +snRNA-seq of human anterior and posterior hippocampus,Resolving cellular and molecular diversity along the hippocampal anterior-to-posterior axis in humans,https://cellxgene.cziscience.com/e/94c41723-b2c4-4b59-a49a-64c9b851903e.cxg/,https://datasets.cellxgene.cziscience.com/3f096be5-dedf-4f7b-a8ed-8d309d18bbde.h5ad,https://doi.org/10.1016/j.neuron.2021.05.003,,T,T,seurat_clusters,other,abbreviations,,Ayhan et al. (2021) Neuron,https://cellxgene.cziscience.com/collections/f17b9205-f61f-4a0f-a65a-73ba91c50ade,Normal,Adult +Single-nucleus transcriptome data from the dlPFC,Molecular and cellular evolution of the primate dorsolateral prefrontal cortex,https://cellxgene.cziscience.com/e/3c361813-5d5e-4868-bfe5-e7591e7b5381.cxg/,https://datasets.cellxgene.cziscience.com/d25fc11f-5790-4a62-af67-e6e58816194e.h5ad,DOI: 10.1126/science.abo7257,,T,T,PMI,other,abbreviations,,Ma et al. (2022) Science,https://cellxgene.cziscience.com/collections/e1fa9900-3fc9-4b57-9dce-c95724c88716,Normal,Adult +Single-nucleus transcriptome data from the dlPFC,Molecular and cellular evolution of the primate dorsolateral prefrontal cortex,https://cellxgene.cziscience.com/e/3c361813-5d5e-4868-bfe5-e7591e7b5381.cxg/,https://datasets.cellxgene.cziscience.com/d25fc11f-5790-4a62-af67-e6e58816194e.h5ad,DOI: 10.1126/science.abo7257,,T,T,Source,other,abbreviations,,Ma et al. (2022) Science,https://cellxgene.cziscience.com/collections/e1fa9900-3fc9-4b57-9dce-c95724c88716,Normal,Adult +Single-nucleus transcriptome data from the dlPFC,Molecular and cellular evolution of the primate dorsolateral prefrontal cortex,https://cellxgene.cziscience.com/e/3c361813-5d5e-4868-bfe5-e7591e7b5381.cxg/,https://datasets.cellxgene.cziscience.com/d25fc11f-5790-4a62-af67-e6e58816194e.h5ad,DOI: 10.1126/science.abo7257,,T,T,author_age_year,other,abbreviations,,Ma et al. (2022) Science,https://cellxgene.cziscience.com/collections/e1fa9900-3fc9-4b57-9dce-c95724c88716,Normal,Adult +Single-nucleus transcriptome data from the dlPFC,Molecular and cellular evolution of the primate dorsolateral prefrontal cortex,https://cellxgene.cziscience.com/e/3c361813-5d5e-4868-bfe5-e7591e7b5381.cxg/,https://datasets.cellxgene.cziscience.com/d25fc11f-5790-4a62-af67-e6e58816194e.h5ad,DOI: 10.1126/science.abo7257,,T,T,class,cell types,abbreviations,,Ma et al. (2022) Science,https://cellxgene.cziscience.com/collections/e1fa9900-3fc9-4b57-9dce-c95724c88716,Normal,Adult +Single-nucleus transcriptome data from the dlPFC,Molecular and cellular evolution of the primate dorsolateral prefrontal cortex,https://cellxgene.cziscience.com/e/3c361813-5d5e-4868-bfe5-e7591e7b5381.cxg/,https://datasets.cellxgene.cziscience.com/d25fc11f-5790-4a62-af67-e6e58816194e.h5ad,DOI: 10.1126/science.abo7257,,T,T,subclass,cell types,abbreviations,,Ma et al. (2022) Science,https://cellxgene.cziscience.com/collections/e1fa9900-3fc9-4b57-9dce-c95724c88716,Normal,Adult +Single-nucleus transcriptome data from the dlPFC,Molecular and cellular evolution of the primate dorsolateral prefrontal cortex,https://cellxgene.cziscience.com/e/3c361813-5d5e-4868-bfe5-e7591e7b5381.cxg/,https://datasets.cellxgene.cziscience.com/d25fc11f-5790-4a62-af67-e6e58816194e.h5ad,DOI: 10.1126/science.abo7257,,T,T,subtype,cell types,abbreviations,,Ma et al. (2022) Science,https://cellxgene.cziscience.com/collections/e1fa9900-3fc9-4b57-9dce-c95724c88716,Normal,Adult +Single-nucleus transcriptome data from the dlPFC,Molecular and cellular evolution of the primate dorsolateral prefrontal cortex,https://cellxgene.cziscience.com/e/3c361813-5d5e-4868-bfe5-e7591e7b5381.cxg/,https://datasets.cellxgene.cziscience.com/d25fc11f-5790-4a62-af67-e6e58816194e.h5ad,DOI: 10.1126/science.abo7257,,T,T,tech_rep,other,abbreviations,,Ma et al. (2022) Science,https://cellxgene.cziscience.com/collections/e1fa9900-3fc9-4b57-9dce-c95724c88716,Normal,Adult +BrainAgingSpatialAtlas_MERFISH,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/cb34cb2d-aee2-4272-86ed-f8e1af870e52.cxg/,https://datasets.cellxgene.cziscience.com/2330673b-b5dc-4690-bbbe-8f409362df31.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,age,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/cb34cb2d-aee2-4272-86ed-f8e1af870e52.cxg/,https://datasets.cellxgene.cziscience.com/2330673b-b5dc-4690-bbbe-8f409362df31.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,cell_type_annot,cell types,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/cb34cb2d-aee2-4272-86ed-f8e1af870e52.cxg/,https://datasets.cellxgene.cziscience.com/2330673b-b5dc-4690-bbbe-8f409362df31.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,center_x,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/cb34cb2d-aee2-4272-86ed-f8e1af870e52.cxg/,https://datasets.cellxgene.cziscience.com/2330673b-b5dc-4690-bbbe-8f409362df31.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,center_y,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/cb34cb2d-aee2-4272-86ed-f8e1af870e52.cxg/,https://datasets.cellxgene.cziscience.com/2330673b-b5dc-4690-bbbe-8f409362df31.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,clust_annot,cell types,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/cb34cb2d-aee2-4272-86ed-f8e1af870e52.cxg/,https://datasets.cellxgene.cziscience.com/2330673b-b5dc-4690-bbbe-8f409362df31.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,fov,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/cb34cb2d-aee2-4272-86ed-f8e1af870e52.cxg/,https://datasets.cellxgene.cziscience.com/2330673b-b5dc-4690-bbbe-8f409362df31.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,max_x,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/cb34cb2d-aee2-4272-86ed-f8e1af870e52.cxg/,https://datasets.cellxgene.cziscience.com/2330673b-b5dc-4690-bbbe-8f409362df31.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,max_y,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/cb34cb2d-aee2-4272-86ed-f8e1af870e52.cxg/,https://datasets.cellxgene.cziscience.com/2330673b-b5dc-4690-bbbe-8f409362df31.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,min_x,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/cb34cb2d-aee2-4272-86ed-f8e1af870e52.cxg/,https://datasets.cellxgene.cziscience.com/2330673b-b5dc-4690-bbbe-8f409362df31.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,min_y,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/cb34cb2d-aee2-4272-86ed-f8e1af870e52.cxg/,https://datasets.cellxgene.cziscience.com/2330673b-b5dc-4690-bbbe-8f409362df31.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,slice,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_Imputed,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/e9a7ead8-c994-4178-b4e4-db951f1bd31a.cxg/,https://datasets.cellxgene.cziscience.com/f44ed5dd-9f5b-4cf4-b6c3-5874ee8ab2f0.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,age,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_Imputed,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/e9a7ead8-c994-4178-b4e4-db951f1bd31a.cxg/,https://datasets.cellxgene.cziscience.com/f44ed5dd-9f5b-4cf4-b6c3-5874ee8ab2f0.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,cell_type_annot,cell types,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_Imputed,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/e9a7ead8-c994-4178-b4e4-db951f1bd31a.cxg/,https://datasets.cellxgene.cziscience.com/f44ed5dd-9f5b-4cf4-b6c3-5874ee8ab2f0.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,center_x,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_Imputed,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/e9a7ead8-c994-4178-b4e4-db951f1bd31a.cxg/,https://datasets.cellxgene.cziscience.com/f44ed5dd-9f5b-4cf4-b6c3-5874ee8ab2f0.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,center_y,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_Imputed,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/e9a7ead8-c994-4178-b4e4-db951f1bd31a.cxg/,https://datasets.cellxgene.cziscience.com/f44ed5dd-9f5b-4cf4-b6c3-5874ee8ab2f0.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,clust_annot,cell types,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_Imputed,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/e9a7ead8-c994-4178-b4e4-db951f1bd31a.cxg/,https://datasets.cellxgene.cziscience.com/f44ed5dd-9f5b-4cf4-b6c3-5874ee8ab2f0.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,fov,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_Imputed,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/e9a7ead8-c994-4178-b4e4-db951f1bd31a.cxg/,https://datasets.cellxgene.cziscience.com/f44ed5dd-9f5b-4cf4-b6c3-5874ee8ab2f0.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,max_x,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_Imputed,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/e9a7ead8-c994-4178-b4e4-db951f1bd31a.cxg/,https://datasets.cellxgene.cziscience.com/f44ed5dd-9f5b-4cf4-b6c3-5874ee8ab2f0.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,max_y,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_Imputed,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/e9a7ead8-c994-4178-b4e4-db951f1bd31a.cxg/,https://datasets.cellxgene.cziscience.com/f44ed5dd-9f5b-4cf4-b6c3-5874ee8ab2f0.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,min_x,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_Imputed,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/e9a7ead8-c994-4178-b4e4-db951f1bd31a.cxg/,https://datasets.cellxgene.cziscience.com/f44ed5dd-9f5b-4cf4-b6c3-5874ee8ab2f0.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,min_y,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_Imputed,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/e9a7ead8-c994-4178-b4e4-db951f1bd31a.cxg/,https://datasets.cellxgene.cziscience.com/f44ed5dd-9f5b-4cf4-b6c3-5874ee8ab2f0.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,slice,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH_LPS,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/c20f1b97-0d47-4192-af0a-1e012621f8d9.cxg/,https://datasets.cellxgene.cziscience.com/b63887bb-da4a-4b6b-9da1-19a05227f7eb.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,age,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH_LPS,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/c20f1b97-0d47-4192-af0a-1e012621f8d9.cxg/,https://datasets.cellxgene.cziscience.com/b63887bb-da4a-4b6b-9da1-19a05227f7eb.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,cell_type_annot,cell types,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH_LPS,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/c20f1b97-0d47-4192-af0a-1e012621f8d9.cxg/,https://datasets.cellxgene.cziscience.com/b63887bb-da4a-4b6b-9da1-19a05227f7eb.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,clust_annot,cell types,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_MERFISH_LPS,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/c20f1b97-0d47-4192-af0a-1e012621f8d9.cxg/,https://datasets.cellxgene.cziscience.com/b63887bb-da4a-4b6b-9da1-19a05227f7eb.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,slice,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_snRNAseq,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/3bbb6cf9-72b9-41be-b568-656de6eb18b5.cxg/,https://datasets.cellxgene.cziscience.com/59a999ca-31b3-4f0e-a4e6-70c240435e01.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,age,other,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_snRNAseq,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/3bbb6cf9-72b9-41be-b568-656de6eb18b5.cxg/,https://datasets.cellxgene.cziscience.com/59a999ca-31b3-4f0e-a4e6-70c240435e01.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,cell_type_annot,cell types,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +BrainAgingSpatialAtlas_snRNAseq,Molecular and spatial signatures of mouse brain aging at single-cell resolution,https://cellxgene.cziscience.com/e/3bbb6cf9-72b9-41be-b568-656de6eb18b5.cxg/,https://datasets.cellxgene.cziscience.com/59a999ca-31b3-4f0e-a4e6-70c240435e01.h5ad,https://doi.org/10.1016/j.cell.2022.12.010,,T,T,clust_annot,cell types,abbreviations,,Allen et al. (2022) Cell,https://cellxgene.cziscience.com/collections/31937775-0602-4e52-a799-b6acdd2bac2e,Normal,Adult +snmCT-seq of human dorsolateral prefrontal cortex (Brodmann area 46),Neuron type-specific effects of human aging and sex on DNA methylation and transcription,https://cellxgene.cziscience.com/e/43aa19d2-c723-4822-979d-d2f0239835e0.cxg/,https://datasets.cellxgene.cziscience.com/7ac6b92a-cbb7-472b-9380-27b5c4714702.h5ad,https://doi.org/10.1101/2023.11.11.566717,,T,T,age_category,other,normal,,Chien et al. (2023) bioRxiv,https://cellxgene.cziscience.com/collections/91c8e321-566f-4f9d-b89e-3a164be654d5,Normal,Adult +snmCT-seq of human dorsolateral prefrontal cortex (Brodmann area 46),Neuron type-specific effects of human aging and sex on DNA methylation and transcription,https://cellxgene.cziscience.com/e/43aa19d2-c723-4822-979d-d2f0239835e0.cxg/,https://datasets.cellxgene.cziscience.com/7ac6b92a-cbb7-472b-9380-27b5c4714702.h5ad,https://doi.org/10.1101/2023.11.11.566717,,T,T,annot_level0,cell types,abbreviations,,Chien et al. (2023) bioRxiv,https://cellxgene.cziscience.com/collections/91c8e321-566f-4f9d-b89e-3a164be654d5,Normal,Adult +snmCT-seq of human dorsolateral prefrontal cortex (Brodmann area 46),Neuron type-specific effects of human aging and sex on DNA methylation and transcription,https://cellxgene.cziscience.com/e/43aa19d2-c723-4822-979d-d2f0239835e0.cxg/,https://datasets.cellxgene.cziscience.com/7ac6b92a-cbb7-472b-9380-27b5c4714702.h5ad,https://doi.org/10.1101/2023.11.11.566717,,T,T,annot_level1,cell types,abbreviations,,Chien et al. (2023) bioRxiv,https://cellxgene.cziscience.com/collections/91c8e321-566f-4f9d-b89e-3a164be654d5,Normal,Adult +snmCT-seq of human dorsolateral prefrontal cortex (Brodmann area 46),Neuron type-specific effects of human aging and sex on DNA methylation and transcription,https://cellxgene.cziscience.com/e/43aa19d2-c723-4822-979d-d2f0239835e0.cxg/,https://datasets.cellxgene.cziscience.com/7ac6b92a-cbb7-472b-9380-27b5c4714702.h5ad,https://doi.org/10.1101/2023.11.11.566717,,T,T,annot_level3,cell types,abbreviations,,Chien et al. (2023) bioRxiv,https://cellxgene.cziscience.com/collections/91c8e321-566f-4f9d-b89e-3a164be654d5,Normal,Adult +snmCT-seq of human dorsolateral prefrontal cortex (Brodmann area 46),Neuron type-specific effects of human aging and sex on DNA methylation and transcription,https://cellxgene.cziscience.com/e/43aa19d2-c723-4822-979d-d2f0239835e0.cxg/,https://datasets.cellxgene.cziscience.com/7ac6b92a-cbb7-472b-9380-27b5c4714702.h5ad,https://doi.org/10.1101/2023.11.11.566717,,T,T,author_cell_type,cell types,abbreviations,,Chien et al. (2023) bioRxiv,https://cellxgene.cziscience.com/collections/91c8e321-566f-4f9d-b89e-3a164be654d5,Normal,Adult +snmCT-seq of human dorsolateral prefrontal cortex (Brodmann area 46),Neuron type-specific effects of human aging and sex on DNA methylation and transcription,https://cellxgene.cziscience.com/e/43aa19d2-c723-4822-979d-d2f0239835e0.cxg/,https://datasets.cellxgene.cziscience.com/7ac6b92a-cbb7-472b-9380-27b5c4714702.h5ad,https://doi.org/10.1101/2023.11.11.566717,,T,T,batch,other,abbreviations,,Chien et al. (2023) bioRxiv,https://cellxgene.cziscience.com/collections/91c8e321-566f-4f9d-b89e-3a164be654d5,Normal,Adult +snmCT-seq of human dorsolateral prefrontal cortex (Brodmann area 46),Neuron type-specific effects of human aging and sex on DNA methylation and transcription,https://cellxgene.cziscience.com/e/43aa19d2-c723-4822-979d-d2f0239835e0.cxg/,https://datasets.cellxgene.cziscience.com/7ac6b92a-cbb7-472b-9380-27b5c4714702.h5ad,https://doi.org/10.1101/2023.11.11.566717,,T,T,donor_cause_of_death,other,normal,,Chien et al. (2023) bioRxiv,https://cellxgene.cziscience.com/collections/91c8e321-566f-4f9d-b89e-3a164be654d5,Normal,Adult +snmCT-seq of human dorsolateral prefrontal cortex (Brodmann area 46),Neuron type-specific effects of human aging and sex on DNA methylation and transcription,https://cellxgene.cziscience.com/e/43aa19d2-c723-4822-979d-d2f0239835e0.cxg/,https://datasets.cellxgene.cziscience.com/7ac6b92a-cbb7-472b-9380-27b5c4714702.h5ad,https://doi.org/10.1101/2023.11.11.566717,,T,T,sample_source,other,normal,,Chien et al. (2023) bioRxiv,https://cellxgene.cziscience.com/collections/91c8e321-566f-4f9d-b89e-3a164be654d5,Normal,Adult +snmCT-seq of human dorsolateral prefrontal cortex (Brodmann area 46),Neuron type-specific effects of human aging and sex on DNA methylation and transcription,https://cellxgene.cziscience.com/e/43aa19d2-c723-4822-979d-d2f0239835e0.cxg/,https://datasets.cellxgene.cziscience.com/7ac6b92a-cbb7-472b-9380-27b5c4714702.h5ad,https://doi.org/10.1101/2023.11.11.566717,,T,T,sample_uuid,other,abbreviations,,Chien et al. (2023) bioRxiv,https://cellxgene.cziscience.com/collections/91c8e321-566f-4f9d-b89e-3a164be654d5,Normal,Adult +snmCT-seq of human dorsolateral prefrontal cortex (Brodmann area 46),Neuron type-specific effects of human aging and sex on DNA methylation and transcription,https://cellxgene.cziscience.com/e/43aa19d2-c723-4822-979d-d2f0239835e0.cxg/,https://datasets.cellxgene.cziscience.com/7ac6b92a-cbb7-472b-9380-27b5c4714702.h5ad,https://doi.org/10.1101/2023.11.11.566717,,T,T,suspension_uuid,other,abbreviations,,Chien et al. (2023) bioRxiv,https://cellxgene.cziscience.com/collections/91c8e321-566f-4f9d-b89e-3a164be654d5,Normal,Adult +snmCT-seq of human dorsolateral prefrontal cortex (Brodmann area 46),Neuron type-specific effects of human aging and sex on DNA methylation and transcription,https://cellxgene.cziscience.com/e/43aa19d2-c723-4822-979d-d2f0239835e0.cxg/,https://datasets.cellxgene.cziscience.com/7ac6b92a-cbb7-472b-9380-27b5c4714702.h5ad,https://doi.org/10.1101/2023.11.11.566717,,T,T,tissue_handling_interval,other,abbreviations,,Chien et al. (2023) bioRxiv,https://cellxgene.cziscience.com/collections/91c8e321-566f-4f9d-b89e-3a164be654d5,Normal,Adult +A single-cell multi-omic atlas spanning the adult rhesus macaque brain,A single-cell transcriptomic atlas spanning the adult rhesus macaque brain,https://cellxgene.cziscience.com/e/d87ba7ec-fddf-4141-abfd-1d69e8427a42.cxg/,https://datasets.cellxgene.cziscience.com/541de42d-9188-45f0-ba93-15b57eddd665.h5ad,DOI: 10.1126/sciadv.adh1914,,T,T,cell_class,cell types,normal,,Chiou et al. (2023) Sci. Adv.,https://cellxgene.cziscience.com/collections/8c4bcf0d-b4df-45c7-888c-74fb0013e9e7,Normal,Adult +A single-cell multi-omic atlas spanning the adult rhesus macaque brain,A single-cell transcriptomic atlas spanning the adult rhesus macaque brain,https://cellxgene.cziscience.com/e/d87ba7ec-fddf-4141-abfd-1d69e8427a42.cxg/,https://datasets.cellxgene.cziscience.com/541de42d-9188-45f0-ba93-15b57eddd665.h5ad,DOI: 10.1126/sciadv.adh1914,,T,T,cell_cluster,other,abbreviations,,Chiou et al. (2023) Sci. Adv.,https://cellxgene.cziscience.com/collections/8c4bcf0d-b4df-45c7-888c-74fb0013e9e8,Normal,Adult +A single-cell multi-omic atlas spanning the adult rhesus macaque brain,A single-cell transcriptomic atlas spanning the adult rhesus macaque brain,https://cellxgene.cziscience.com/e/d87ba7ec-fddf-4141-abfd-1d69e8427a42.cxg/,https://datasets.cellxgene.cziscience.com/541de42d-9188-45f0-ba93-15b57eddd665.h5ad,DOI: 10.1126/sciadv.adh1914,,T,T,cell_subcluster,cell types,normal,,Chiou et al. (2023) Sci. Adv.,https://cellxgene.cziscience.com/collections/8c4bcf0d-b4df-45c7-888c-74fb0013e9e9,Normal,Adult +A single-cell multi-omic atlas spanning the adult rhesus macaque brain,A single-cell transcriptomic atlas spanning the adult rhesus macaque brain,https://cellxgene.cziscience.com/e/d87ba7ec-fddf-4141-abfd-1d69e8427a42.cxg/,https://datasets.cellxgene.cziscience.com/541de42d-9188-45f0-ba93-15b57eddd665.h5ad,DOI: 10.1126/sciadv.adh1914,,T,T,hemisphere,other,normal,,Chiou et al. (2023) Sci. Adv.,https://cellxgene.cziscience.com/collections/8c4bcf0d-b4df-45c7-888c-74fb0013e9e10,Normal,Adult +A single-cell multi-omic atlas spanning the adult rhesus macaque brain,A single-cell transcriptomic atlas spanning the adult rhesus macaque brain,https://cellxgene.cziscience.com/e/d87ba7ec-fddf-4141-abfd-1d69e8427a42.cxg/,https://datasets.cellxgene.cziscience.com/541de42d-9188-45f0-ba93-15b57eddd665.h5ad,DOI: 10.1126/sciadv.adh1914,,T,T,isolation_site,other,abbreviations,,Chiou et al. (2023) Sci. Adv.,https://cellxgene.cziscience.com/collections/8c4bcf0d-b4df-45c7-888c-74fb0013e9e11,Normal,Adult +A single-cell multi-omic atlas spanning the adult rhesus macaque brain,A single-cell transcriptomic atlas spanning the adult rhesus macaque brain,https://cellxgene.cziscience.com/e/d87ba7ec-fddf-4141-abfd-1d69e8427a42.cxg/,https://datasets.cellxgene.cziscience.com/541de42d-9188-45f0-ba93-15b57eddd665.h5ad,DOI: 10.1126/sciadv.adh1914,,T,T,nuclei_suspension_id,other,abbreviations,,Chiou et al. (2023) Sci. Adv.,https://cellxgene.cziscience.com/collections/8c4bcf0d-b4df-45c7-888c-74fb0013e9e12,Normal,Adult +A single-cell multi-omic atlas spanning the adult rhesus macaque brain,A single-cell transcriptomic atlas spanning the adult rhesus macaque brain,https://cellxgene.cziscience.com/e/d87ba7ec-fddf-4141-abfd-1d69e8427a42.cxg/,https://datasets.cellxgene.cziscience.com/541de42d-9188-45f0-ba93-15b57eddd665.h5ad,DOI: 10.1126/sciadv.adh1914,,T,T,region,other,abbreviations,,Chiou et al. (2023) Sci. Adv.,https://cellxgene.cziscience.com/collections/8c4bcf0d-b4df-45c7-888c-74fb0013e9e13,Normal,Adult +A single-cell multi-omic atlas spanning the adult rhesus macaque brain,A single-cell transcriptomic atlas spanning the adult rhesus macaque brain,https://cellxgene.cziscience.com/e/d87ba7ec-fddf-4141-abfd-1d69e8427a42.cxg/,https://datasets.cellxgene.cziscience.com/541de42d-9188-45f0-ba93-15b57eddd665.h5ad,DOI: 10.1126/sciadv.adh1914,,T,T,region_class,other,normal,,Chiou et al. (2023) Sci. Adv.,https://cellxgene.cziscience.com/collections/8c4bcf0d-b4df-45c7-888c-74fb0013e9e14,Normal,Adult +A single-cell multi-omic atlas spanning the adult rhesus macaque brain,A single-cell transcriptomic atlas spanning the adult rhesus macaque brain,https://cellxgene.cziscience.com/e/d87ba7ec-fddf-4141-abfd-1d69e8427a42.cxg/,https://datasets.cellxgene.cziscience.com/541de42d-9188-45f0-ba93-15b57eddd665.h5ad,DOI: 10.1126/sciadv.adh1914,,T,T,region_name,other,normal,,Chiou et al. (2023) Sci. Adv.,https://cellxgene.cziscience.com/collections/8c4bcf0d-b4df-45c7-888c-74fb0013e9e15,Normal,Adult +A single-cell multi-omic atlas spanning the adult rhesus macaque brain,A single-cell transcriptomic atlas spanning the adult rhesus macaque brain,https://cellxgene.cziscience.com/e/d87ba7ec-fddf-4141-abfd-1d69e8427a42.cxg/,https://datasets.cellxgene.cziscience.com/541de42d-9188-45f0-ba93-15b57eddd665.h5ad,DOI: 10.1126/sciadv.adh1914,,T,T,region_subclass,other,normal,,Chiou et al. (2023) Sci. Adv.,https://cellxgene.cziscience.com/collections/8c4bcf0d-b4df-45c7-888c-74fb0013e9e16,Normal,Adult +A single-cell multi-omic atlas spanning the adult rhesus macaque brain,A single-cell transcriptomic atlas spanning the adult rhesus macaque brain,https://cellxgene.cziscience.com/e/d87ba7ec-fddf-4141-abfd-1d69e8427a42.cxg/,https://datasets.cellxgene.cziscience.com/541de42d-9188-45f0-ba93-15b57eddd665.h5ad,DOI: 10.1126/sciadv.adh1914,,T,T,sequencing_run_id,other,abbreviations,,Chiou et al. (2023) Sci. Adv.,https://cellxgene.cziscience.com/collections/8c4bcf0d-b4df-45c7-888c-74fb0013e9e17,Normal,Adult +A single-cell multi-omic atlas spanning the adult rhesus macaque brain,A single-cell transcriptomic atlas spanning the adult rhesus macaque brain,https://cellxgene.cziscience.com/e/d87ba7ec-fddf-4141-abfd-1d69e8427a42.cxg/,https://datasets.cellxgene.cziscience.com/541de42d-9188-45f0-ba93-15b57eddd665.h5ad,DOI: 10.1126/sciadv.adh1914,,T,T,social_group,other,abbreviations,,Chiou et al. (2023) Sci. Adv.,https://cellxgene.cziscience.com/collections/8c4bcf0d-b4df-45c7-888c-74fb0013e9e18,Normal,Adult +A transcriptomic atlas of the mouse cerebellum,A transcriptomic atlas of the mouse cerebellum reveals regional specializations and novel cell types,https://cellxgene.cziscience.com/e/e0ed3c55-aff6-4bb7-b6ff-98a2d90b890c.cxg/,https://datasets.cellxgene.cziscience.com/1d6fb189-21a5-4e9b-9082-b6fe225374a9.h5ad,https://doi.org/10.1038/s41586-021-03220-z,,T,T,BICCN_subclass_label,cell types,normal,,Kozareva et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/f70ebd97-b3bc-44fe-849d-c18e08fe773d,Normal,Adult +A transcriptomic atlas of the mouse cerebellum,A transcriptomic atlas of the mouse cerebellum reveals regional specializations and novel cell types,https://cellxgene.cziscience.com/e/e0ed3c55-aff6-4bb7-b6ff-98a2d90b890c.cxg/,https://datasets.cellxgene.cziscience.com/1d6fb189-21a5-4e9b-9082-b6fe225374a9.h5ad,https://doi.org/10.1038/s41586-021-03220-z,,T,T,biosample_id,other,normal,,Kozareva et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/f70ebd97-b3bc-44fe-849d-c18e08fe773d,Normal,Adult +A transcriptomic atlas of the mouse cerebellum,A transcriptomic atlas of the mouse cerebellum reveals regional specializations and novel cell types,https://cellxgene.cziscience.com/e/e0ed3c55-aff6-4bb7-b6ff-98a2d90b890c.cxg/,https://datasets.cellxgene.cziscience.com/1d6fb189-21a5-4e9b-9082-b6fe225374a9.h5ad,https://doi.org/10.1038/s41586-021-03220-z,,T,T,cluster,cell types,normal,,Kozareva et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/f70ebd97-b3bc-44fe-849d-c18e08fe773d,Normal,Adult +A transcriptomic atlas of the mouse cerebellum,A transcriptomic atlas of the mouse cerebellum reveals regional specializations and novel cell types,https://cellxgene.cziscience.com/e/e0ed3c55-aff6-4bb7-b6ff-98a2d90b890c.cxg/,https://datasets.cellxgene.cziscience.com/1d6fb189-21a5-4e9b-9082-b6fe225374a9.h5ad,https://doi.org/10.1038/s41586-021-03220-z,,T,T,nGene,other,normal,,Kozareva et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/f70ebd97-b3bc-44fe-849d-c18e08fe773d,Normal,Adult +A transcriptomic atlas of the mouse cerebellum,A transcriptomic atlas of the mouse cerebellum reveals regional specializations and novel cell types,https://cellxgene.cziscience.com/e/e0ed3c55-aff6-4bb7-b6ff-98a2d90b890c.cxg/,https://datasets.cellxgene.cziscience.com/1d6fb189-21a5-4e9b-9082-b6fe225374a9.h5ad,https://doi.org/10.1038/s41586-021-03220-z,,T,T,nUMI,other,normal,,Kozareva et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/f70ebd97-b3bc-44fe-849d-c18e08fe773d,Normal,Adult +A transcriptomic atlas of the mouse cerebellum,A transcriptomic atlas of the mouse cerebellum reveals regional specializations and novel cell types,https://cellxgene.cziscience.com/e/e0ed3c55-aff6-4bb7-b6ff-98a2d90b890c.cxg/,https://datasets.cellxgene.cziscience.com/1d6fb189-21a5-4e9b-9082-b6fe225374a9.h5ad,https://doi.org/10.1038/s41586-021-03220-z,,T,T,organ_region,other,abbreviations,,Kozareva et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/f70ebd97-b3bc-44fe-849d-c18e08fe773d,Normal,Adult +A transcriptomic atlas of the mouse cerebellum,A transcriptomic atlas of the mouse cerebellum reveals regional specializations and novel cell types,https://cellxgene.cziscience.com/e/e0ed3c55-aff6-4bb7-b6ff-98a2d90b890c.cxg/,https://datasets.cellxgene.cziscience.com/1d6fb189-21a5-4e9b-9082-b6fe225374a9.h5ad,https://doi.org/10.1038/s41586-021-03220-z,,T,T,organ_region__ontology_label,other,normal,,Kozareva et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/f70ebd97-b3bc-44fe-849d-c18e08fe773d,Normal,Adult +A transcriptomic atlas of the mouse cerebellum,A transcriptomic atlas of the mouse cerebellum reveals regional specializations and novel cell types,https://cellxgene.cziscience.com/e/e0ed3c55-aff6-4bb7-b6ff-98a2d90b890c.cxg/,https://datasets.cellxgene.cziscience.com/1d6fb189-21a5-4e9b-9082-b6fe225374a9.h5ad,https://doi.org/10.1038/s41586-021-03220-z,,T,T,region,other,abbreviations,,Kozareva et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/f70ebd97-b3bc-44fe-849d-c18e08fe773d,Normal,Adult +A transcriptomic atlas of the mouse cerebellum,A transcriptomic atlas of the mouse cerebellum reveals regional specializations and novel cell types,https://cellxgene.cziscience.com/e/e0ed3c55-aff6-4bb7-b6ff-98a2d90b890c.cxg/,https://datasets.cellxgene.cziscience.com/1d6fb189-21a5-4e9b-9082-b6fe225374a9.h5ad,https://doi.org/10.1038/s41586-021-03220-z,,T,T,subcluster,cell types,normal,,Kozareva et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/f70ebd97-b3bc-44fe-849d-c18e08fe773d,Normal,Adult +Non-neuronal cells — An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum.,An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum,https://cellxgene.cziscience.com/e/b22a3a55-9a35-434e-93e1-f2483037f33c.cxg/,https://datasets.cellxgene.cziscience.com/39f2c06e-4a70-4936-a645-7d6a61fc0c00.h5ad,https://doi.org/10.1038/s41586-021-03604-1,,T,T,BICCN_subclass_label,cell types,abbreviations,,Li et al. (2021) Nature,https://cellxgene.cziscience.com/collections/5e469121-c203-4775-962d-dcf2e5d6a472,Normal,Adult +Non-neuronal cells — An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum.,An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum,https://cellxgene.cziscience.com/e/b22a3a55-9a35-434e-93e1-f2483037f33c.cxg/,https://datasets.cellxgene.cziscience.com/39f2c06e-4a70-4936-a645-7d6a61fc0c00.h5ad,https://doi.org/10.1038/s41586-021-03604-1,,T,T,DissectionRegion,other,abbreviations,,Li et al. (2021) Nature,https://cellxgene.cziscience.com/collections/5e469121-c203-4775-962d-dcf2e5d6a473,Normal,Adult +Non-neuronal cells — An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum.,An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum,https://cellxgene.cziscience.com/e/b22a3a55-9a35-434e-93e1-f2483037f33c.cxg/,https://datasets.cellxgene.cziscience.com/39f2c06e-4a70-4936-a645-7d6a61fc0c00.h5ad,https://doi.org/10.1038/s41586-021-03604-1,,T,T,MajorRegion,other,abbreviations,,Li et al. (2021) Nature,https://cellxgene.cziscience.com/collections/5e469121-c203-4775-962d-dcf2e5d6a474,Normal,Adult +Non-neuronal cells — An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum.,An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum,https://cellxgene.cziscience.com/e/b22a3a55-9a35-434e-93e1-f2483037f33c.cxg/,https://datasets.cellxgene.cziscience.com/39f2c06e-4a70-4936-a645-7d6a61fc0c00.h5ad,https://doi.org/10.1038/s41586-021-03604-1,,T,T,RegionName,other,abbreviations,,Li et al. (2021) Nature,https://cellxgene.cziscience.com/collections/5e469121-c203-4775-962d-dcf2e5d6a475,Normal,Adult +Non-neuronal cells — An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum.,An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum,https://cellxgene.cziscience.com/e/b22a3a55-9a35-434e-93e1-f2483037f33c.cxg/,https://datasets.cellxgene.cziscience.com/39f2c06e-4a70-4936-a645-7d6a61fc0c00.h5ad,https://doi.org/10.1038/s41586-021-03604-1,,T,T,Slice,other,abbreviations,,Li et al. (2021) Nature,https://cellxgene.cziscience.com/collections/5e469121-c203-4775-962d-dcf2e5d6a476,Normal,Adult +Non-neuronal cells — An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum.,An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum,https://cellxgene.cziscience.com/e/b22a3a55-9a35-434e-93e1-f2483037f33c.cxg/,https://datasets.cellxgene.cziscience.com/39f2c06e-4a70-4936-a645-7d6a61fc0c00.h5ad,https://doi.org/10.1038/s41586-021-03604-1,,T,T,SubRegion,other,abbreviations,,Li et al. (2021) Nature,https://cellxgene.cziscience.com/collections/5e469121-c203-4775-962d-dcf2e5d6a477,Normal,Adult +Non-neuronal cells — An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum.,An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum,https://cellxgene.cziscience.com/e/b22a3a55-9a35-434e-93e1-f2483037f33c.cxg/,https://datasets.cellxgene.cziscience.com/39f2c06e-4a70-4936-a645-7d6a61fc0c00.h5ad,https://doi.org/10.1038/s41586-021-03604-1,,T,T,replicate,other,abbreviations,,Li et al. (2021) Nature,https://cellxgene.cziscience.com/collections/5e469121-c203-4775-962d-dcf2e5d6a478,Normal,Adult +Non-neuronal cells — An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum.,An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum,https://cellxgene.cziscience.com/e/b22a3a55-9a35-434e-93e1-f2483037f33c.cxg/,https://datasets.cellxgene.cziscience.com/39f2c06e-4a70-4936-a645-7d6a61fc0c00.h5ad,https://doi.org/10.1038/s41586-021-03604-1,,T,T,sample,other,abbreviations,,Li et al. (2021) Nature,https://cellxgene.cziscience.com/collections/5e469121-c203-4775-962d-dcf2e5d6a479,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,AllcPath,other,normal,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,BICCN_class_label,cell types,abbreviations,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,BICCN_cluster_label,cell types,abbreviations,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,BICCN_subclass_label,cell types,abbreviations,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,DetailRegion,other,abbreviations,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,L1CellClass,cell types,abbreviations,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,MajorRegion,other,abbreviations,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,Plate,other,normal,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,Pos96,other,normal,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,PotentialOverlap (MMB),other,abbreviations,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,Region,other,abbreviations,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,RegionName,other,abbreviations,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,Replicate,other,normal,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,SubRegion,other,abbreviations,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,SubRegionColor,other,normal,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,index_name,other,normal,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +DNA Methylation (CGN) Atlas of the Mouse Brain at Single-Cell Resolution,DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution,https://cellxgene.cziscience.com/e/7bdddd90-9428-47e2-bb80-e77d8b1cc96e.cxg/,https://datasets.cellxgene.cziscience.com/10bb8aaa-ebc6-4026-94ae-a33ac16b5366.h5ad,https://doi.org/10.1038/s41586-020-03182-8,,T,T,uid,other,normal,,Liu et al. (2021) Nature,https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6,Normal,Adult +A scRNA-seq atlas of immune cells at the CNS borders,Humoral immunity at the brain borders in homeostasis,https://cellxgene.cziscience.com/e/58b01044-c5e5-4b0f-8a2d-6ebf951e01ff.cxg/,https://datasets.cellxgene.cziscience.com/9ad2790f-25e5-44d7-8828-ff5aadeba589.h5ad,https://doi.org/10.1016/j.coi.2022.102188,,T,T,author_cell_type,cell types,abbreviations,,Posner et al. (2022) Current Opinion in Immunology,https://cellxgene.cziscience.com/collections/e9eec7f5-8519-42f6-99b4-6dbd9cc5ef03,Normal,Adult +A scRNA-seq atlas of immune cells at the CNS borders,Humoral immunity at the brain borders in homeostasis,https://cellxgene.cziscience.com/e/58b01044-c5e5-4b0f-8a2d-6ebf951e01ff.cxg/,https://datasets.cellxgene.cziscience.com/9ad2790f-25e5-44d7-8828-ff5aadeba589.h5ad,https://doi.org/10.1016/j.coi.2022.102188,,T,T,sample_id,other,normal,,Posner et al. (2022) Current Opinion in Immunology,https://cellxgene.cziscience.com/collections/e9eec7f5-8519-42f6-99b4-6dbd9cc5ef03,Normal,Adult +A scRNA-seq atlas of immune cells at the CNS borders,Humoral immunity at the brain borders in homeostasis,https://cellxgene.cziscience.com/e/58b01044-c5e5-4b0f-8a2d-6ebf951e01ff.cxg/,https://datasets.cellxgene.cziscience.com/9ad2790f-25e5-44d7-8828-ff5aadeba589.h5ad,https://doi.org/10.1016/j.coi.2022.102188,,T,T,site,other,normal,,Posner et al. (2022) Current Opinion in Immunology,https://cellxgene.cziscience.com/collections/e9eec7f5-8519-42f6-99b4-6dbd9cc5ef03,Normal,Adult +A scRNA-seq atlas of immune cells at the CNS borders,Humoral immunity at the brain borders in homeostasis,https://cellxgene.cziscience.com/e/58b01044-c5e5-4b0f-8a2d-6ebf951e01ff.cxg/,https://datasets.cellxgene.cziscience.com/9ad2790f-25e5-44d7-8828-ff5aadeba589.h5ad,https://doi.org/10.1016/j.coi.2022.102188,,T,T,study,other,normal,,Posner et al. (2022) Current Opinion in Immunology,https://cellxgene.cziscience.com/collections/e9eec7f5-8519-42f6-99b4-6dbd9cc5ef03,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,ALMVISp top-3,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,BICCN_cluster_label,cell types,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,BICCN_subclass_label,cell types,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Cre,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Date,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Exclusion reasons,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Inferred layer,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Mouse date of birth,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Mouse genotype,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,RNA family,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,RNA type top-3,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Sample,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Slice,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Targeted layer,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Trace,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +Excitatory neurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d.cxg/,https://datasets.cellxgene.cziscience.com/460d368c-9147-4716-8674-76bf0795ba85.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,User,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,ALMVISp top-3,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,BICCN_cluster_label,cell types,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,BICCN_subclass_label,cell types,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Cre,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Date,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Exclusion reasons,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Inferred layer,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Mouse date of birth,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Mouse genotype,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,RNA family,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,RNA type top-3,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Sample,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Slice,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Targeted layer,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Trace,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +CGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/9bb9596d-f23f-4558-912f-d4dc7d52721b.cxg/,https://datasets.cellxgene.cziscience.com/d7e86fbd-f606-48c1-af99-a12c10a615f2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,User,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,ALMVISp top-3,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,BICCN_cluster_label,cell types,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,BICCN_subclass_label,cell types,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Cre,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Date,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Exclusion reasons,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Inferred layer,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Mouse date of birth,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Mouse genotype,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,RNA family,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,RNA type top-3,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Sample,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Slice,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Targeted layer,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Trace,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +MGE-derived interneurons integrated with 10X sequencing MOp data,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/42ff5b55-b848-4f4c-b7cb-b8aac107841c.cxg/,https://datasets.cellxgene.cziscience.com/3d04a6eb-2cd8-4546-9f79-61f739fe503e.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,User,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,ALMVISp top-3,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,BICCN_cluster_label,cell types,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,BICCN_subclass_label,cell types,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Cre,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Date,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Exclusion reasons,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Inferred layer,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Mouse date of birth,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Mouse genotype,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,RNA family,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,RNA type top-3,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Sample,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Slice,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Targeted layer,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Trace,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/bf6a5c78-5a2e-4e34-93f3-7be5d127d879.cxg/,https://datasets.cellxgene.cziscience.com/1dbc9400-aeb1-44b4-ba4a-a738c368570f.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,User,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,ALMVISp top-3,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,BICCN_cluster_label,cell types,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,BICCN_subclass_label,cell types,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Cre,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Date,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Exclusion reasons,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Inferred layer,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Mouse date of birth,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Mouse genotype,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,RNA family,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,RNA type top-3,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Sample,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Slice,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Targeted layer,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Trace,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/341a0702-9d26-4d8a-b047-ab475f3b492e.cxg/,https://datasets.cellxgene.cziscience.com/bc474348-6dbd-483a-acb7-f295d1521fa2.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,User,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,ALMVISp top-3,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,BICCN_cluster_label,cell types,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,BICCN_subclass_label,cell types,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Cre,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Date,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Exclusion reasons,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Inferred layer,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Mouse date of birth,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Mouse genotype,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,RNA family,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,RNA type top-3,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Sample,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Slice,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Targeted layer,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,Trace,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +All cells with electrophysiological and morphological recordings,Phenotypic variation of transcriptomic cell types in mouse motor cortex,https://cellxgene.cziscience.com/e/8f98c236-43f0-4dc4-985b-c304499f7b44.cxg/,https://datasets.cellxgene.cziscience.com/070d3916-633e-43af-bcc6-30358a327161.h5ad,https://doi.org/10.1038/s41586-020-2907-3,,T,T,User,other,abbreviations,,Scala et al. (2021) Nature,https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,Author_CellType,cell types,abbreviations,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,Author_Class_Curated,cell types,normal,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,Batch_ID,other,abbreviations,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,C185_named,cell types,abbreviations,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,C25_named,cell types,abbreviations,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,C286_named,cell types,abbreviations,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,C465_named,cell types,abbreviations,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,C66_named,cell types,abbreviations,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,C7_named,cell types,abbreviations,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,Dataset,other,normal,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,Region_summarized,other,normal,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,SRA_ID,other,abbreviations,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,HypoMap – a unified single cell gene expression atlas of the murine hypothalamus,https://cellxgene.cziscience.com/e/dbb4e1ed-d820-4e83-981f-88ef7eb55a35.cxg/,https://datasets.cellxgene.cziscience.com/250192f0-94d8-4e26-91cb-afe7e360605e.h5ad,https://doi.org/10.1038/s42255-022-00657-y,,T,T,Sample_ID,other,abbreviations,,Steuernagel et al. (2022) Nat Metab,https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36,Normal,Adult +Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,https://cellxgene.cziscience.com/e/3a15ab1c-c36c-4842-9a3e-47e6ffd0ba6f.cxg/,https://datasets.cellxgene.cziscience.com/e48806af-87d1-45ae-843a-c7ee06eac672.h5ad,https://doi.org/10.1038/nn.4216,,T,T,BICCN_class_label,cell types,normal,,Tasic et al. (2016) Nat Neurosci,https://cellxgene.cziscience.com/collections/a3c37598-b8e8-47db-92a9-eb91a77c9529,Normal,Adult +Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,https://cellxgene.cziscience.com/e/3a15ab1c-c36c-4842-9a3e-47e6ffd0ba6f.cxg/,https://datasets.cellxgene.cziscience.com/e48806af-87d1-45ae-843a-c7ee06eac672.h5ad,https://doi.org/10.1038/nn.4216,,T,T,BICCN_cluster_label,cell types,abbreviations,,Tasic et al. (2016) Nat Neurosci,https://cellxgene.cziscience.com/collections/a3c37598-b8e8-47db-92a9-eb91a77c9529,Normal,Adult +Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,https://cellxgene.cziscience.com/e/3a15ab1c-c36c-4842-9a3e-47e6ffd0ba6f.cxg/,https://datasets.cellxgene.cziscience.com/e48806af-87d1-45ae-843a-c7ee06eac672.h5ad,https://doi.org/10.1038/nn.4216,,T,T,collection_date,other,normal,,Tasic et al. (2016) Nat Neurosci,https://cellxgene.cziscience.com/collections/a3c37598-b8e8-47db-92a9-eb91a77c9529,Normal,Adult +Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,https://cellxgene.cziscience.com/e/3a15ab1c-c36c-4842-9a3e-47e6ffd0ba6f.cxg/,https://datasets.cellxgene.cziscience.com/e48806af-87d1-45ae-843a-c7ee06eac672.h5ad,https://doi.org/10.1038/nn.4216,,T,T,cre,other,abbreviations,,Tasic et al. (2016) Nat Neurosci,https://cellxgene.cziscience.com/collections/a3c37598-b8e8-47db-92a9-eb91a77c9529,Normal,Adult +Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,https://cellxgene.cziscience.com/e/3a15ab1c-c36c-4842-9a3e-47e6ffd0ba6f.cxg/,https://datasets.cellxgene.cziscience.com/e48806af-87d1-45ae-843a-c7ee06eac672.h5ad,https://doi.org/10.1038/nn.4216,,T,T,layer_dissectoin,other,abbreviations,,Tasic et al. (2016) Nat Neurosci,https://cellxgene.cziscience.com/collections/a3c37598-b8e8-47db-92a9-eb91a77c9529,Normal,Adult +Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,https://cellxgene.cziscience.com/e/3a15ab1c-c36c-4842-9a3e-47e6ffd0ba6f.cxg/,https://datasets.cellxgene.cziscience.com/e48806af-87d1-45ae-843a-c7ee06eac672.h5ad,https://doi.org/10.1038/nn.4216,,T,T,sequencing_type,other,abbreviations,,Tasic et al. (2016) Nat Neurosci,https://cellxgene.cziscience.com/collections/a3c37598-b8e8-47db-92a9-eb91a77c9529,Normal,Adult +Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,Adult mouse cortical cell taxonomy revealed by single cell transcriptomics,https://cellxgene.cziscience.com/e/3a15ab1c-c36c-4842-9a3e-47e6ffd0ba6f.cxg/,https://datasets.cellxgene.cziscience.com/e48806af-87d1-45ae-843a-c7ee06eac672.h5ad,https://doi.org/10.1038/nn.4216,,T,T,short_name,other,abbreviations,,Tasic et al. (2016) Nat Neurosci,https://cellxgene.cziscience.com/collections/a3c37598-b8e8-47db-92a9-eb91a77c9529,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,BICCN_class_label,cell types,normal,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,BICCN_subclass_label,cell types,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,brain_hemisphere,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,brain_region,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,brain_subregion,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,cluster,cell types,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,core_intermediate_call,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,driver_lines,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,eye_condition,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,facs_container,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,facs_date,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,facs_sort_criteria,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,genotype,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,injection_exclusion_criterion,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,injection_label_direction,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,injection_material,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,injection_primary,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,injection_secondary,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,injection_tract,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,library_prep_set,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,reporter_lines,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,rna_amplification_pcr_cycles,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,rna_amplification_set,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,seq_batch,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Shared and distinct transcriptomic cell types across neocortical areas,Shared and distinct transcriptomic cell types across neocortical areas,https://cellxgene.cziscience.com/e/28c696bb-9549-434b-9340-dc745a846f9a.cxg/,https://datasets.cellxgene.cziscience.com/7ac1b9e2-91f8-4a62-93a8-54638f2e618e.h5ad,https://doi.org/10.1038/s41586-018-0654-5,,T,T,seq_tube,other,abbreviations,,Tasic et al. (2018) Nature,https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f,Normal,Adult +Brain non-myeloid cells - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/66ff82b4-9380-469c-bc4b-cfa08eacd325.cxg/,https://datasets.cellxgene.cziscience.com/0054013c-290b-437e-b98e-642aa77d6ebc.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,FACS.selection,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +Brain non-myeloid cells - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/66ff82b4-9380-469c-bc4b-cfa08eacd325.cxg/,https://datasets.cellxgene.cziscience.com/0054013c-290b-437e-b98e-642aa77d6ebc.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,age,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +Brain non-myeloid cells - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/66ff82b4-9380-469c-bc4b-cfa08eacd325.cxg/,https://datasets.cellxgene.cziscience.com/0054013c-290b-437e-b98e-642aa77d6ebc.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,cell,cell types,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +Brain non-myeloid cells - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/66ff82b4-9380-469c-bc4b-cfa08eacd325.cxg/,https://datasets.cellxgene.cziscience.com/0054013c-290b-437e-b98e-642aa77d6ebc.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,free_annotation,cell types,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +Brain non-myeloid cells - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/66ff82b4-9380-469c-bc4b-cfa08eacd325.cxg/,https://datasets.cellxgene.cziscience.com/0054013c-290b-437e-b98e-642aa77d6ebc.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,leiden,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +Brain non-myeloid cells - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/66ff82b4-9380-469c-bc4b-cfa08eacd325.cxg/,https://datasets.cellxgene.cziscience.com/0054013c-290b-437e-b98e-642aa77d6ebc.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,louvain,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +Brain non-myeloid cells - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/66ff82b4-9380-469c-bc4b-cfa08eacd325.cxg/,https://datasets.cellxgene.cziscience.com/0054013c-290b-437e-b98e-642aa77d6ebc.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,subtissue,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +All - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/f16a8f4d-bc97-43c5-a2f6-bbda952e4c5c.cxg/,https://datasets.cellxgene.cziscience.com/3310476e-ee9d-4179-9446-df5d073f38d8.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,FACS.selection,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +All - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/f16a8f4d-bc97-43c5-a2f6-bbda952e4c5c.cxg/,https://datasets.cellxgene.cziscience.com/3310476e-ee9d-4179-9446-df5d073f38d8.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,age,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +All - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/f16a8f4d-bc97-43c5-a2f6-bbda952e4c5c.cxg/,https://datasets.cellxgene.cziscience.com/3310476e-ee9d-4179-9446-df5d073f38d8.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,batch,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +All - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/f16a8f4d-bc97-43c5-a2f6-bbda952e4c5c.cxg/,https://datasets.cellxgene.cziscience.com/3310476e-ee9d-4179-9446-df5d073f38d8.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,free_annotation,cell types,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +All - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/f16a8f4d-bc97-43c5-a2f6-bbda952e4c5c.cxg/,https://datasets.cellxgene.cziscience.com/3310476e-ee9d-4179-9446-df5d073f38d8.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,leiden,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +All - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/f16a8f4d-bc97-43c5-a2f6-bbda952e4c5c.cxg/,https://datasets.cellxgene.cziscience.com/3310476e-ee9d-4179-9446-df5d073f38d8.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,louvain,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +All - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/f16a8f4d-bc97-43c5-a2f6-bbda952e4c5c.cxg/,https://datasets.cellxgene.cziscience.com/3310476e-ee9d-4179-9446-df5d073f38d8.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,method,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +All - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/f16a8f4d-bc97-43c5-a2f6-bbda952e4c5c.cxg/,https://datasets.cellxgene.cziscience.com/3310476e-ee9d-4179-9446-df5d073f38d8.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,subtissue,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +All - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/f16a8f4d-bc97-43c5-a2f6-bbda952e4c5c.cxg/,https://datasets.cellxgene.cziscience.com/3310476e-ee9d-4179-9446-df5d073f38d8.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,tissue_FACS_droplet,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +All - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/f16a8f4d-bc97-43c5-a2f6-bbda952e4c5c.cxg/,https://datasets.cellxgene.cziscience.com/3310476e-ee9d-4179-9446-df5d073f38d8.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,tissue_free_annotation,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +All - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse,Tabula Muris Senis,https://cellxgene.cziscience.com/e/f16a8f4d-bc97-43c5-a2f6-bbda952e4c5c.cxg/,https://datasets.cellxgene.cziscience.com/3310476e-ee9d-4179-9446-df5d073f38d8.h5ad,https://doi.org/10.1038/s41586-020-2496-1,,T,T,tissue_original,other,abbreviations,,The Tabula Muris Consortium et al. (2020) Nature,https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb,Normal,Adult +DNA methylation of brain cells -- CG methylation of Inhibitory and Subcortical Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/f0939ae1-0877-42b2-bc0e-3249a42c2c0f.cxg/,https://datasets.cellxgene.cziscience.com/4a04c010-6fc1-440a-8b87-f12fefd5543a.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_MajorType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Inhibitory and Subcortical Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/f0939ae1-0877-42b2-bc0e-3249a42c2c0f.cxg/,https://datasets.cellxgene.cziscience.com/4a04c010-6fc1-440a-8b87-f12fefd5543a.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_Region,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Inhibitory and Subcortical Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/f0939ae1-0877-42b2-bc0e-3249a42c2c0f.cxg/,https://datasets.cellxgene.cziscience.com/4a04c010-6fc1-440a-8b87-f12fefd5543a.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_SubType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Inhibitory and Subcortical Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/f0939ae1-0877-42b2-bc0e-3249a42c2c0f.cxg/,https://datasets.cellxgene.cziscience.com/4a04c010-6fc1-440a-8b87-f12fefd5543a.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_pool,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Inhibitory and Subcortical Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/52f0b078-0fb7-4cdb-81f8-d1bcf7b4468b.cxg/,https://datasets.cellxgene.cziscience.com/969408c1-7fdf-4abe-bf6a-9d662e620c16.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_MajorType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Inhibitory and Subcortical Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/52f0b078-0fb7-4cdb-81f8-d1bcf7b4468b.cxg/,https://datasets.cellxgene.cziscience.com/969408c1-7fdf-4abe-bf6a-9d662e620c16.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_Region,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Inhibitory and Subcortical Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/52f0b078-0fb7-4cdb-81f8-d1bcf7b4468b.cxg/,https://datasets.cellxgene.cziscience.com/969408c1-7fdf-4abe-bf6a-9d662e620c16.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_SubType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Inhibitory and Subcortical Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/52f0b078-0fb7-4cdb-81f8-d1bcf7b4468b.cxg/,https://datasets.cellxgene.cziscience.com/969408c1-7fdf-4abe-bf6a-9d662e620c16.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_pool,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Excitatory Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/38e5738d-3870-433b-858a-5c364f322439.cxg/,https://datasets.cellxgene.cziscience.com/1c6e54ca-ef0c-4acc-9891-d3b7d2cd7a0e.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_MajorType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Excitatory Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/38e5738d-3870-433b-858a-5c364f322439.cxg/,https://datasets.cellxgene.cziscience.com/1c6e54ca-ef0c-4acc-9891-d3b7d2cd7a0e.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_Region,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Excitatory Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/38e5738d-3870-433b-858a-5c364f322439.cxg/,https://datasets.cellxgene.cziscience.com/1c6e54ca-ef0c-4acc-9891-d3b7d2cd7a0e.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_SubType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Excitatory Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/38e5738d-3870-433b-858a-5c364f322439.cxg/,https://datasets.cellxgene.cziscience.com/1c6e54ca-ef0c-4acc-9891-d3b7d2cd7a0e.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_pool,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Excitatory Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/346c5aad-b034-4248-8cbe-0a05fd634b9c.cxg/,https://datasets.cellxgene.cziscience.com/be497f34-bf74-4cf0-8094-e6f8729b9fa4.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_MajorType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Excitatory Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/346c5aad-b034-4248-8cbe-0a05fd634b9c.cxg/,https://datasets.cellxgene.cziscience.com/be497f34-bf74-4cf0-8094-e6f8729b9fa4.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_Region,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Excitatory Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/346c5aad-b034-4248-8cbe-0a05fd634b9c.cxg/,https://datasets.cellxgene.cziscience.com/be497f34-bf74-4cf0-8094-e6f8729b9fa4.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_SubType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Excitatory Neurons (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/346c5aad-b034-4248-8cbe-0a05fd634b9c.cxg/,https://datasets.cellxgene.cziscience.com/be497f34-bf74-4cf0-8094-e6f8729b9fa4.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_pool,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Non-neuronal Cells (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/d6f3c096-a6f0-4e67-91ad-514bd286f13e.cxg/,https://datasets.cellxgene.cziscience.com/a31264ed-a890-4409-9d93-cfb5e9cfcc71.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_MajorType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Non-neuronal Cells (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/d6f3c096-a6f0-4e67-91ad-514bd286f13e.cxg/,https://datasets.cellxgene.cziscience.com/a31264ed-a890-4409-9d93-cfb5e9cfcc71.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_Region,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Non-neuronal Cells (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/d6f3c096-a6f0-4e67-91ad-514bd286f13e.cxg/,https://datasets.cellxgene.cziscience.com/a31264ed-a890-4409-9d93-cfb5e9cfcc71.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_SubType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Non-neuronal Cells (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/d6f3c096-a6f0-4e67-91ad-514bd286f13e.cxg/,https://datasets.cellxgene.cziscience.com/a31264ed-a890-4409-9d93-cfb5e9cfcc71.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_pool,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Non-neuronal Cells (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/8f83f50e-c091-4095-8456-a7acf6c9d423.cxg/,https://datasets.cellxgene.cziscience.com/781d308e-69cc-4129-8c2f-b370091a8cab.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_MajorType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Non-neuronal Cells (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/8f83f50e-c091-4095-8456-a7acf6c9d423.cxg/,https://datasets.cellxgene.cziscience.com/781d308e-69cc-4129-8c2f-b370091a8cab.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_Region,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Non-neuronal Cells (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/8f83f50e-c091-4095-8456-a7acf6c9d423.cxg/,https://datasets.cellxgene.cziscience.com/781d308e-69cc-4129-8c2f-b370091a8cab.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_SubType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Non-neuronal Cells (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/8f83f50e-c091-4095-8456-a7acf6c9d423.cxg/,https://datasets.cellxgene.cziscience.com/781d308e-69cc-4129-8c2f-b370091a8cab.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_pool,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Non-neuronal Cells (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/0500e103-38db-456d-9c3f-b96b8a693ab2.cxg/,https://datasets.cellxgene.cziscience.com/a991b447-9473-4978-b2bd-190cf4a26825.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_MajorType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Non-neuronal Cells (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/0500e103-38db-456d-9c3f-b96b8a693ab2.cxg/,https://datasets.cellxgene.cziscience.com/a991b447-9473-4978-b2bd-190cf4a26825.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_Region,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Non-neuronal Cells (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/0500e103-38db-456d-9c3f-b96b8a693ab2.cxg/,https://datasets.cellxgene.cziscience.com/a991b447-9473-4978-b2bd-190cf4a26825.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_SubType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Non-neuronal Cells (snmC-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/0500e103-38db-456d-9c3f-b96b8a693ab2.cxg/,https://datasets.cellxgene.cziscience.com/a991b447-9473-4978-b2bd-190cf4a26825.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_pool,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Excitatory Neurons (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/3ed61f1e-bd31-411e-b4aa-9729e8437732.cxg/,https://datasets.cellxgene.cziscience.com/f62628d2-3c79-4c17-a77c-a09897080360.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_MajorType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Excitatory Neurons (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/3ed61f1e-bd31-411e-b4aa-9729e8437732.cxg/,https://datasets.cellxgene.cziscience.com/f62628d2-3c79-4c17-a77c-a09897080360.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_Region,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Excitatory Neurons (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/3ed61f1e-bd31-411e-b4aa-9729e8437732.cxg/,https://datasets.cellxgene.cziscience.com/f62628d2-3c79-4c17-a77c-a09897080360.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_SubType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Excitatory Neurons (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/3ed61f1e-bd31-411e-b4aa-9729e8437732.cxg/,https://datasets.cellxgene.cziscience.com/f62628d2-3c79-4c17-a77c-a09897080360.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_pool,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Inhibitory and Subcortical Neurons (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/a12d95f7-480f-4c8a-bf24-302175b27bc4.cxg/,https://datasets.cellxgene.cziscience.com/43b216d8-b988-4ade-8263-55c45f1944db.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_MajorType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Inhibitory and Subcortical Neurons (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/a12d95f7-480f-4c8a-bf24-302175b27bc4.cxg/,https://datasets.cellxgene.cziscience.com/43b216d8-b988-4ade-8263-55c45f1944db.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_Region,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Inhibitory and Subcortical Neurons (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/a12d95f7-480f-4c8a-bf24-302175b27bc4.cxg/,https://datasets.cellxgene.cziscience.com/43b216d8-b988-4ade-8263-55c45f1944db.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_SubType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- non-CG methylation of Inhibitory and Subcortical Neurons (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/a12d95f7-480f-4c8a-bf24-302175b27bc4.cxg/,https://datasets.cellxgene.cziscience.com/43b216d8-b988-4ade-8263-55c45f1944db.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_pool,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Inhibitory and Subcortical Neurons (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/33da10b0-9c1d-4c82-9b14-c67cdcf9fae5.cxg/,https://datasets.cellxgene.cziscience.com/e4ee90d9-a9b1-4b12-a2e9-9cbce715ee06.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_MajorType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Inhibitory and Subcortical Neurons (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/33da10b0-9c1d-4c82-9b14-c67cdcf9fae5.cxg/,https://datasets.cellxgene.cziscience.com/e4ee90d9-a9b1-4b12-a2e9-9cbce715ee06.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_Region,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Inhibitory and Subcortical Neurons (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/33da10b0-9c1d-4c82-9b14-c67cdcf9fae5.cxg/,https://datasets.cellxgene.cziscience.com/e4ee90d9-a9b1-4b12-a2e9-9cbce715ee06.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_SubType,cell types,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +DNA methylation of brain cells -- CG methylation of Inhibitory and Subcortical Neurons (snm3C-seq),Single-Cell DNA Methylation and 3D Genome Human Brain Atlas,https://cellxgene.cziscience.com/e/33da10b0-9c1d-4c82-9b14-c67cdcf9fae5.cxg/,https://datasets.cellxgene.cziscience.com/e4ee90d9-a9b1-4b12-a2e9-9cbce715ee06.h5ad,https://doi.org/10.1126/science.adf5357,,T,T,_pool,other,abbreviations,,Tian et al. (2023) Science,https://cellxgene.cziscience.com/collections/fdebfda9-bb9a-4b4b-97e5-651097ea07b0,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (10x),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/d7291f04-fbbb-4d65-990a-f01fa44e915b.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,class_label,cell types,normal,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (10x),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/d7291f04-fbbb-4d65-990a-f01fa44e915b.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,cluster_label,cell types,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (10x),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/d7291f04-fbbb-4d65-990a-f01fa44e915b.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,cluster_order,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (10x),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/d7291f04-fbbb-4d65-990a-f01fa44e915b.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,full_genotype_label,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (10x),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/d7291f04-fbbb-4d65-990a-f01fa44e915b.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,neighborhood_label,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (10x),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/d7291f04-fbbb-4d65-990a-f01fa44e915b.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,region_label,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (10x),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/d7291f04-fbbb-4d65-990a-f01fa44e915b.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,subclass_label,cell types,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,class_label,cell types,normal,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,cluster_label,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,cluster_order,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,cortical_layer_label,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,facs_population_plan_label,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,full_genotype_label,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,injection_materials_id,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,injection_method_id,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,injection_roi_id,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,neighborhood_label,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,orig_study,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,region_label,other,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +Single-cell RNA-seq for all cortical & hippocampal regions (SMART-Seq v4),A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation,https://cellxgene.cziscience.com/e/812fa7bd-db15-4357-b2c9-efc8e1eb0450.cxg/,https://datasets.cellxgene.cziscience.com/fdd2ff73-9163-4648-90da-b218573c2bee.h5ad,https://doi.org/10.1016/j.cell.2021.04.021,,T,T,subclass_label,cell types,abbreviations,,Yao et al. (2021) Cell,https://cellxgene.cziscience.com/collections/e3aa612b-0d7d-4d3f-bbea-b8972a74dd4b,Normal,Adult +An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,https://cellxgene.cziscience.com/e/35081d47-99bf-4507-9541-735428df9a9f.cxg/,https://datasets.cellxgene.cziscience.com/83bde98b-fc88-4147-a217-1f1ffa508dd2.h5ad,https://doi.org/10.1038/s41586-021-03500-8,,T,T,BICCN_class_label,cell types,normal,,Yao et al. (2021) Nature,https://cellxgene.cziscience.com/collections/ae1420fe-6630-46ed-8b3d-cc6056a66467,Normal,Adult +An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,https://cellxgene.cziscience.com/e/35081d47-99bf-4507-9541-735428df9a9f.cxg/,https://datasets.cellxgene.cziscience.com/83bde98b-fc88-4147-a217-1f1ffa508dd2.h5ad,https://doi.org/10.1038/s41586-021-03500-8,,T,T,BICCN_cluster_label,cell types,abbreviations,,Yao et al. (2021) Nature,https://cellxgene.cziscience.com/collections/ae1420fe-6630-46ed-8b3d-cc6056a66467,Normal,Adult +An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,https://cellxgene.cziscience.com/e/35081d47-99bf-4507-9541-735428df9a9f.cxg/,https://datasets.cellxgene.cziscience.com/83bde98b-fc88-4147-a217-1f1ffa508dd2.h5ad,https://doi.org/10.1038/s41586-021-03500-8,,T,T,BICCN_project,other,normal,,Yao et al. (2021) Nature,https://cellxgene.cziscience.com/collections/ae1420fe-6630-46ed-8b3d-cc6056a66467,Normal,Adult +An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,https://cellxgene.cziscience.com/e/35081d47-99bf-4507-9541-735428df9a9f.cxg/,https://datasets.cellxgene.cziscience.com/83bde98b-fc88-4147-a217-1f1ffa508dd2.h5ad,https://doi.org/10.1038/s41586-021-03500-8,,T,T,BICCN_subclass_label,cell types,abbreviations,,Yao et al. (2021) Nature,https://cellxgene.cziscience.com/collections/ae1420fe-6630-46ed-8b3d-cc6056a66467,Normal,Adult +An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,https://cellxgene.cziscience.com/e/35081d47-99bf-4507-9541-735428df9a9f.cxg/,https://datasets.cellxgene.cziscience.com/83bde98b-fc88-4147-a217-1f1ffa508dd2.h5ad,https://doi.org/10.1038/s41586-021-03500-8,,T,T,QC,other,abbreviations,,Yao et al. (2021) Nature,https://cellxgene.cziscience.com/collections/ae1420fe-6630-46ed-8b3d-cc6056a66467,Normal,Adult +An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,https://cellxgene.cziscience.com/e/35081d47-99bf-4507-9541-735428df9a9f.cxg/,https://datasets.cellxgene.cziscience.com/83bde98b-fc88-4147-a217-1f1ffa508dd2.h5ad,https://doi.org/10.1038/s41586-021-03500-8,,T,T,cluster_color,other,normal,,Yao et al. (2021) Nature,https://cellxgene.cziscience.com/collections/ae1420fe-6630-46ed-8b3d-cc6056a66467,Normal,Adult +An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types,https://cellxgene.cziscience.com/e/35081d47-99bf-4507-9541-735428df9a9f.cxg/,https://datasets.cellxgene.cziscience.com/83bde98b-fc88-4147-a217-1f1ffa508dd2.h5ad,https://doi.org/10.1038/s41586-021-03500-8,,T,T,temp_class_label,cell types,abbreviations,,Yao et al. (2021) Nature,https://cellxgene.cziscience.com/collections/ae1420fe-6630-46ed-8b3d-cc6056a66467,Normal,Adult +"Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics","Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics",https://cellxgene.cziscience.com/e/257adc73-8152-414b-a2c7-73861b8e0c0a.cxg/,https://datasets.cellxgene.cziscience.com/06a7ffec-2697-4d6f-96f6-d00a34bedb3d.h5ad,https://doi.org/10.1101/2020.06.04.105700,,T,T,BICCN_class_label,cell types,normal,,Zhang et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/9132fae8-bdfe-480f-9e45-45bc77f320b3,Normal,Adult +"Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics","Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics",https://cellxgene.cziscience.com/e/257adc73-8152-414b-a2c7-73861b8e0c0a.cxg/,https://datasets.cellxgene.cziscience.com/06a7ffec-2697-4d6f-96f6-d00a34bedb3d.h5ad,https://doi.org/10.1101/2020.06.04.105700,,T,T,BICCN_cluster_label,cell types,abbreviations,,Zhang et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/9132fae8-bdfe-480f-9e45-45bc77f320b3,Normal,Adult +"Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics","Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics",https://cellxgene.cziscience.com/e/257adc73-8152-414b-a2c7-73861b8e0c0a.cxg/,https://datasets.cellxgene.cziscience.com/06a7ffec-2697-4d6f-96f6-d00a34bedb3d.h5ad,https://doi.org/10.1101/2020.06.04.105700,,T,T,BICCN_subclass_label,cell types,abbreviations,,Zhang et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/9132fae8-bdfe-480f-9e45-45bc77f320b3,Normal,Adult +"Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics","Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics",https://cellxgene.cziscience.com/e/257adc73-8152-414b-a2c7-73861b8e0c0a.cxg/,https://datasets.cellxgene.cziscience.com/06a7ffec-2697-4d6f-96f6-d00a34bedb3d.h5ad,https://doi.org/10.1101/2020.06.04.105700,,T,T,sample_id,other,abbreviations,,Zhang et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/9132fae8-bdfe-480f-9e45-45bc77f320b3,Normal,Adult +"Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics","Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics",https://cellxgene.cziscience.com/e/257adc73-8152-414b-a2c7-73861b8e0c0a.cxg/,https://datasets.cellxgene.cziscience.com/06a7ffec-2697-4d6f-96f6-d00a34bedb3d.h5ad,https://doi.org/10.1101/2020.06.04.105700,,T,T,slice_id,other,abbreviations,,Zhang et al. (2020) bioRxiv,https://cellxgene.cziscience.com/collections/9132fae8-bdfe-480f-9e45-45bc77f320b3,Normal,Adult +WB_MERFISH_animal1_coronal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/73c39ba5-17dc-4630-b99a-0d43164a3945.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,brain_section_label,other,normal,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal1_coronal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/73c39ba5-17dc-4630-b99a-0d43164a3945.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,ccf_region_name,other,normal,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal1_coronal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/73c39ba5-17dc-4630-b99a-0d43164a3945.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,cluster_id_transfer,other,normal,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal1_coronal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/73c39ba5-17dc-4630-b99a-0d43164a3945.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,high_quality_transfer,other,normal,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal1_coronal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/73c39ba5-17dc-4630-b99a-0d43164a3945.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,major_brain_region,other,normal,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal1_coronal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/73c39ba5-17dc-4630-b99a-0d43164a3945.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,subclass_transfer,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal3_sagittal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/20de7fd1-ab21-45b8-a1e2-f7b36261f8e2.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,brain_section_label,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal3_sagittal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/20de7fd1-ab21-45b8-a1e2-f7b36261f8e2.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,ccf_region_name,other,normal,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal3_sagittal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/20de7fd1-ab21-45b8-a1e2-f7b36261f8e2.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,cluster_id_transfer,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal3_sagittal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/20de7fd1-ab21-45b8-a1e2-f7b36261f8e2.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,high_quality_transfer,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal3_sagittal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/20de7fd1-ab21-45b8-a1e2-f7b36261f8e2.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,major_brain_region,other,normal,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal3_sagittal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/20de7fd1-ab21-45b8-a1e2-f7b36261f8e2.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,subclass_transfe,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal2_coronal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/836fc2fc-c376-49a8-8265-01a33dfa0dc7.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,brain_section_label,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal2_coronal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/836fc2fc-c376-49a8-8265-01a33dfa0dc7.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,ccf_region_name,other,normal,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal2_coronal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/836fc2fc-c376-49a8-8265-01a33dfa0dc7.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,cluster_id_transfer,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal2_coronal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/836fc2fc-c376-49a8-8265-01a33dfa0dc7.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,high_quality_transfer,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal2_coronal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/836fc2fc-c376-49a8-8265-01a33dfa0dc7.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,major_brain_region,other,normal,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal2_coronal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/836fc2fc-c376-49a8-8265-01a33dfa0dc7.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,subclass_transfe,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal4_sagittal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/30a2789f-7b76-4414-9c63-1deb3eacdde1.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,brain_section_label,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal4_sagittal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/30a2789f-7b76-4414-9c63-1deb3eacdde1.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,ccf_region_name,other,normal,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal4_sagittal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/30a2789f-7b76-4414-9c63-1deb3eacdde1.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,cluster_id_transfer,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal4_sagittal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/30a2789f-7b76-4414-9c63-1deb3eacdde1.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,high_quality_transfer,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal4_sagittal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/30a2789f-7b76-4414-9c63-1deb3eacdde1.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,major_brain_region,other,normal,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +WB_MERFISH_animal4_sagittal,A molecularly defined and spatially resolved cell atlas of the whole mouse brain,https://cellxgene.cziscience.com/e/30a2789f-7b76-4414-9c63-1deb3eacdde1.cxg/,https://datasets.cellxgene.cziscience.com/31310843-6614-49b3-b2e2-3e85d9be1e66.h5ad,https://doi.org/10.1038/s41586-023-06808-9,,T,T,subclass_transfer,other,abbreviations,,Zhang et al. (2023) Nature,https://cellxgene.cziscience.com/collections/0cca8620-8dee-45d0-aef5-23f032a5cf09,Normal,Adult +All neurons,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/8e10f1c4-8e98-41e5-b65f-8cd89a887122.cxg/,https://datasets.cellxgene.cziscience.com/0bb62fec-0cf1-46e1-9d10-de65a6d4f814.h5ad,DOI: 10.1126/science.add7046,,T,T,ROIGroup,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All neurons,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/8e10f1c4-8e98-41e5-b65f-8cd89a887122.cxg/,https://datasets.cellxgene.cziscience.com/0bb62fec-0cf1-46e1-9d10-de65a6d4f814.h5ad,DOI: 10.1126/science.add7046,,T,T,ROIGroupCoarse,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All neurons,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/8e10f1c4-8e98-41e5-b65f-8cd89a887122.cxg/,https://datasets.cellxgene.cziscience.com/0bb62fec-0cf1-46e1-9d10-de65a6d4f814.h5ad,DOI: 10.1126/science.add7046,,T,T,ROIGroupFine,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All neurons,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/8e10f1c4-8e98-41e5-b65f-8cd89a887122.cxg/,https://datasets.cellxgene.cziscience.com/0bb62fec-0cf1-46e1-9d10-de65a6d4f814.h5ad,DOI: 10.1126/science.add7046,,T,T,cluster_id,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All neurons,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/8e10f1c4-8e98-41e5-b65f-8cd89a887122.cxg/,https://datasets.cellxgene.cziscience.com/0bb62fec-0cf1-46e1-9d10-de65a6d4f814.h5ad,DOI: 10.1126/science.add7046,,T,T,dissection,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All neurons,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/8e10f1c4-8e98-41e5-b65f-8cd89a887122.cxg/,https://datasets.cellxgene.cziscience.com/0bb62fec-0cf1-46e1-9d10-de65a6d4f814.h5ad,DOI: 10.1126/science.add7046,,T,T,roi,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All neurons,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/8e10f1c4-8e98-41e5-b65f-8cd89a887122.cxg/,https://datasets.cellxgene.cziscience.com/0bb62fec-0cf1-46e1-9d10-de65a6d4f814.h5ad,DOI: 10.1126/science.add7046,,T,T,sample_id,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All neurons,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/8e10f1c4-8e98-41e5-b65f-8cd89a887122.cxg/,https://datasets.cellxgene.cziscience.com/0bb62fec-0cf1-46e1-9d10-de65a6d4f814.h5ad,DOI: 10.1126/science.add7046,,T,T,subcluster_id,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All neurons,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/8e10f1c4-8e98-41e5-b65f-8cd89a887122.cxg/,https://datasets.cellxgene.cziscience.com/0bb62fec-0cf1-46e1-9d10-de65a6d4f814.h5ad,DOI: 10.1126/science.add7046,,T,T,supercluster_term,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All non-neuronal cells,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/b165f033-9dec-468a-9248-802fc6902a74.cxg/,https://datasets.cellxgene.cziscience.com/9343817c-5c74-4548-a7d5-01990df5af7a.h5ad,DOI: 10.1126/science.add7046,,T,T,ROIGroup,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All non-neuronal cells,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/b165f033-9dec-468a-9248-802fc6902a74.cxg/,https://datasets.cellxgene.cziscience.com/9343817c-5c74-4548-a7d5-01990df5af7a.h5ad,DOI: 10.1126/science.add7046,,T,T,ROIGroupCoarse,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All non-neuronal cells,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/b165f033-9dec-468a-9248-802fc6902a74.cxg/,https://datasets.cellxgene.cziscience.com/9343817c-5c74-4548-a7d5-01990df5af7a.h5ad,DOI: 10.1126/science.add7046,,T,T,ROIGroupFine,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All non-neuronal cells,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/b165f033-9dec-468a-9248-802fc6902a74.cxg/,https://datasets.cellxgene.cziscience.com/9343817c-5c74-4548-a7d5-01990df5af7a.h5ad,DOI: 10.1126/science.add7046,,T,T,cluster_id,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All non-neuronal cells,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/b165f033-9dec-468a-9248-802fc6902a74.cxg/,https://datasets.cellxgene.cziscience.com/9343817c-5c74-4548-a7d5-01990df5af7a.h5ad,DOI: 10.1126/science.add7046,,T,T,dissection,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All non-neuronal cells,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/b165f033-9dec-468a-9248-802fc6902a74.cxg/,https://datasets.cellxgene.cziscience.com/9343817c-5c74-4548-a7d5-01990df5af7a.h5ad,DOI: 10.1126/science.add7046,,T,T,roi,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All non-neuronal cells,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/b165f033-9dec-468a-9248-802fc6902a74.cxg/,https://datasets.cellxgene.cziscience.com/9343817c-5c74-4548-a7d5-01990df5af7a.h5ad,DOI: 10.1126/science.add7046,,T,T,sample_id,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All non-neuronal cells,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/b165f033-9dec-468a-9248-802fc6902a74.cxg/,https://datasets.cellxgene.cziscience.com/9343817c-5c74-4548-a7d5-01990df5af7a.h5ad,DOI: 10.1126/science.add7046,,T,T,subcluster_id,other,normal,,Siletti et al. (2023) Science,,Normal,Adult +All non-neuronal cells,Human Brain Cell Atlas v1.0,https://cellxgene.cziscience.com/e/b165f033-9dec-468a-9248-802fc6902a74.cxg/,https://datasets.cellxgene.cziscience.com/9343817c-5c74-4548-a7d5-01990df5af7a.h5ad,DOI: 10.1126/science.add7046,,T,T,supercluster_term,other,normal,,Siletti et al. (2023) Science,,Normal,Adult \ No newline at end of file diff --git a/anndata2rdf/src/process.py b/anndata2rdf/src/process.py index 37dacb2..a561ef1 100644 --- a/anndata2rdf/src/process.py +++ b/anndata2rdf/src/process.py @@ -60,4 +60,4 @@ get_dataset_id_from_h5ad_link(dataset), ), ) - # delete_file(dataset_path) + delete_file(dataset_path) diff --git a/cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml b/cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml index 43adebe..1470c19 100644 --- a/cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml +++ b/cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml @@ -17,6 +17,9 @@ neo_node_labelling: - classes: - CL:0000000 label: Cell + - classes: + - PCL:0010001 + label: Cell_cluster curie_map: GITHUB: https://github.com/ diff --git a/cl_kb_pipeline/docker-compose.yml b/cl_kb_pipeline/docker-compose.yml index c45a962..2901082 100644 --- a/cl_kb_pipeline/docker-compose.yml +++ b/cl_kb_pipeline/docker-compose.yml @@ -49,7 +49,7 @@ services: depends_on: triplestore: condition: service_started - obask-collectdata: + anndata2rdf: condition: service_completed_successfully volumes: - ./config/collectdata:/opt/conf_base/config/collectdata From a3c8bbcfe1746b06260a54f14693832bf91c5bf8 Mon Sep 17 00:00:00 2001 From: ugur Date: Sun, 12 May 2024 22:47:44 +0100 Subject: [PATCH 11/18] Added logging to download_dataset_with_url method --- anndata2rdf/src/pull_anndata.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/anndata2rdf/src/pull_anndata.py b/anndata2rdf/src/pull_anndata.py index 317cb2b..776a336 100644 --- a/anndata2rdf/src/pull_anndata.py +++ b/anndata2rdf/src/pull_anndata.py @@ -57,16 +57,16 @@ def download_dataset_with_url(dataset_url: str, file_path: Optional[str] = None) os.path.join("dataset", anndata_file_path), ) if os.path.exists(anndata_file_path): - print("File already exists. Skipping download.") + logger.info(f"File '{anndata_file_path}' already exists. Skipping download.") else: - + logger.info(f"Downloading dataset with URL '{dataset_url} to {anndata_file_path}'...") response = requests.get(dataset_url) if response.status_code == 200: with open(anndata_file_path, 'wb') as f: f.write(response.content) - print("File downloaded successfully.") + logger.info(f"Download complete. File saved at '{anndata_file_path}'.") else: - print("Failed to download the file.") + logger.info(f"Failed to download the dataset with URL '{dataset_url}'...") return anndata_file_path From b0a26b34c18d83b416bf460ee32709d6d9b20929 Mon Sep 17 00:00:00 2001 From: ugur Date: Mon, 20 May 2024 16:04:37 +0100 Subject: [PATCH 12/18] Updated .gitignore --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 6597a4f..64fe260 100644 --- a/.gitignore +++ b/.gitignore @@ -159,3 +159,4 @@ cython_debug/ # and can be added to the global gitignore or merged into this file. For a more nuclear # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ +**/.DS_Store \ No newline at end of file From aae30878508d9fe49b88322261c95355eece6175 Mon Sep 17 00:00:00 2001 From: ugur Date: Mon, 20 May 2024 16:28:43 +0100 Subject: [PATCH 13/18] Clean up --- .github/workflows/schema_validator.yaml | 15 +------------ anndata2rdf/Dockerfile | 5 ----- anndata2rdf/src/process.py | 28 ++++++------------------- anndata2rdf/src/pull_anndata.py | 22 +++++++++++++------ 4 files changed, 23 insertions(+), 47 deletions(-) diff --git a/.github/workflows/schema_validator.yaml b/.github/workflows/schema_validator.yaml index 3dfa3eb..4350e0f 100644 --- a/.github/workflows/schema_validator.yaml +++ b/.github/workflows/schema_validator.yaml @@ -16,7 +16,7 @@ jobs: with: python-version: 3.8 - name: Install dependencies - run: pip install -r "ruamel.yaml==0.17.21" "jsonschema==4.4.0" + run: pip install -r ruamel.yaml==0.17.21 jsonschema==4.4.0 - name: Schema validation id: schema run: | @@ -25,19 +25,6 @@ jobs: if: failure() run: | echo "cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml file failed the schema validation check " > comment.md; cat validation.report >> comment.md -# - name: install Yamale -# run: brew install yamale -# - name: Regex based DL validation -# id: validation -# run: | -# yamale -s schema.yaml config/dumps/neo4j2owl-config.yaml | tee output -# tail -n +4 output > validation.report -# echo ::set-output name=report::$(cat output) -# - name: Prepare DL validator comment -# if: contains(steps.validation.outputs.report, 'Error') -# run: | -# echo "
config/prod/neo4j2owl-config.yaml file failed the regex based DL validation check " > comment.md; cat validation.report >> comment.md -# exit 1 - name: Prepare success comment run: | echo "cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml file passed validation check " > comment.md diff --git a/anndata2rdf/Dockerfile b/anndata2rdf/Dockerfile index dec8360..35942fb 100644 --- a/anndata2rdf/Dockerfile +++ b/anndata2rdf/Dockerfile @@ -7,11 +7,6 @@ RUN apt-get update && apt-get install -y build-essential graphviz libgraphviz-de WORKDIR /app -#ENV VENV="/opt/env" -#ENV PATH="$VENV/bin:$PATH" -# -#RUN python3 -m venv $VENV - COPY requirements.txt ./ RUN pip3 install --upgrade pip RUN pip3 install -r requirements.txt diff --git a/anndata2rdf/src/process.py b/anndata2rdf/src/process.py index a561ef1..31597e3 100644 --- a/anndata2rdf/src/process.py +++ b/anndata2rdf/src/process.py @@ -3,8 +3,12 @@ import sys from csv_parser import generate_author_cell_type_config, write_yaml_file -from pull_anndata import download_dataset_with_id, get_dataset_dict, delete_file, download_dataset_with_url, \ - get_dataset_id_from_h5ad_link +from pull_anndata import ( + get_dataset_dict, + delete_file, + download_dataset_with_url, + get_dataset_id_from_h5ad_link, +) from generate_rdf import generate_rdf_graph logger = logging.getLogger(__name__) @@ -29,28 +33,8 @@ CXG_AUTHOR_CELL_TYPE_CONFIG, ) write_yaml_file(cxg_author_cell_type_yaml, output_file_path) - -# datasets = get_dataset_dict( -# [ -# { -# "CxG_link": "https://cellxgene.cziscience.com/e/8e10f1c4-8e98-41e5-b65f-8cd89a887122.cxg/", -# "author_cell_type_list": [ -# "ROIGroup", -# "ROIGroupCoarse", -# "ROIGroupFine", -# "cluster_id", -# "dissection", -# "roi", -# "sample_id", -# "subcluster_id", -# "supercluster_term", -# ], -# } -# ] -# ) datasets = get_dataset_dict(cxg_author_cell_type_yaml) for dataset, author_cell_types in datasets.items(): - # dataset_path = download_dataset_with_id(dataset) dataset_path = download_dataset_with_url(dataset) generate_rdf_graph( dataset_path, diff --git a/anndata2rdf/src/pull_anndata.py b/anndata2rdf/src/pull_anndata.py index 776a336..68fa53e 100644 --- a/anndata2rdf/src/pull_anndata.py +++ b/anndata2rdf/src/pull_anndata.py @@ -32,7 +32,9 @@ def download_dataset_with_id(dataset_id: str, file_path: Optional[str] = None) - if os.path.exists(anndata_file_path): logger.info(f"File '{anndata_file_path}' already exists. Skipping download.") else: - logger.info(f"Downloading dataset with ID '{dataset_id} to {anndata_file_path}'...") + logger.info( + f"Downloading dataset with ID '{dataset_id} to {anndata_file_path}'..." + ) cellxgene_census.download_source_h5ad(dataset_id, to_path=anndata_file_path) logger.info(f"Download complete. File saved at '{anndata_file_path}'.") return anndata_file_path @@ -51,7 +53,11 @@ def download_dataset_with_url(dataset_url: str, file_path: Optional[str] = None) str: The path to the downloaded file """ - anndata_file_path = f"{get_dataset_id_from_h5ad_link(dataset_url)}.h5ad" if file_path is None else file_path + anndata_file_path = ( + f"{get_dataset_id_from_h5ad_link(dataset_url)}.h5ad" + if file_path is None + else file_path + ) anndata_file_path = os.path.join( os.path.dirname(os.path.abspath(__file__)), os.path.join("dataset", anndata_file_path), @@ -59,10 +65,12 @@ def download_dataset_with_url(dataset_url: str, file_path: Optional[str] = None) if os.path.exists(anndata_file_path): logger.info(f"File '{anndata_file_path}' already exists. Skipping download.") else: - logger.info(f"Downloading dataset with URL '{dataset_url} to {anndata_file_path}'...") + logger.info( + f"Downloading dataset with URL '{dataset_url} to {anndata_file_path}'..." + ) response = requests.get(dataset_url) if response.status_code == 200: - with open(anndata_file_path, 'wb') as f: + with open(anndata_file_path, "wb") as f: f.write(response.content) logger.info(f"Download complete. File saved at '{anndata_file_path}'.") else: @@ -71,7 +79,7 @@ def download_dataset_with_url(dataset_url: str, file_path: Optional[str] = None) def get_dataset_id_from_h5ad_link(dataset_url): - return dataset_url.split('/')[-1].split('.')[0] + return dataset_url.split("/")[-1].split(".")[0] def delete_file(file_name): @@ -88,7 +96,9 @@ def get_dataset_dict(input_source: List[Dict]): cxg_link = config["CxG_link"] if cxg_link.endswith(".cxg"): cxg_id = get_dataset_id_from_link(cxg_link) - cxg_dataset_dict.update({cxg_id.split(".")[0]: config["author_cell_type_list"]}) + cxg_dataset_dict.update( + {cxg_id.split(".")[0]: config["author_cell_type_list"]} + ) else: cxg_dataset_dict.update({cxg_link: config["author_cell_type_list"]}) return cxg_dataset_dict From f96948c7fa1491c9ba4947f9e4b2e9cd93af81b2 Mon Sep 17 00:00:00 2001 From: ugur Date: Mon, 20 May 2024 16:36:33 +0100 Subject: [PATCH 14/18] Updated collectdata config --- cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt b/cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt index 1082525..50b9f29 100644 --- a/cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt +++ b/cl_kb_pipeline/config/collectdata/vfb_fullontologies.txt @@ -1,3 +1,3 @@ http://purl.obolibrary.org/obo/cl/cl-base.owl -file:///out/local_ontologies/325567b8-e698-48ab-9969-ab0b1a2bbb2f.owl -file:///out/local_ontologies/dc6e9e6a-3566-4839-baf9-6cf6616fd20e.owl \ No newline at end of file +https://purl.obolibrary.org/obo/go/go-base.owl +http://purl.obolibrary.org/obo/uberon/uberon-base.owl \ No newline at end of file From daafe50b1e67d2294b2f3e72e9205c933ecb2b04 Mon Sep 17 00:00:00 2001 From: ugur Date: Mon, 20 May 2024 16:42:15 +0100 Subject: [PATCH 15/18] Fixed Install dependencies step --- .github/workflows/schema_validator.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/schema_validator.yaml b/.github/workflows/schema_validator.yaml index 4350e0f..8d3dbe1 100644 --- a/.github/workflows/schema_validator.yaml +++ b/.github/workflows/schema_validator.yaml @@ -16,7 +16,7 @@ jobs: with: python-version: 3.8 - name: Install dependencies - run: pip install -r ruamel.yaml==0.17.21 jsonschema==4.4.0 + run: pip install ruamel.yaml==0.17.21 jsonschema==4.4.0 - name: Schema validation id: schema run: | From 2fc76c21b3395ed38fe7ab77c92a68fb4b034b3d Mon Sep 17 00:00:00 2001 From: ugur Date: Mon, 20 May 2024 16:47:58 +0100 Subject: [PATCH 16/18] Fixed path issue in Schema validation step --- .github/workflows/schema_validator.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/schema_validator.yaml b/.github/workflows/schema_validator.yaml index 8d3dbe1..4d7de31 100644 --- a/.github/workflows/schema_validator.yaml +++ b/.github/workflows/schema_validator.yaml @@ -20,7 +20,7 @@ jobs: - name: Schema validation id: schema run: | - python src/test_neo2owl_config.py + python cl_kb_pipeline/src/test_neo2owl_config.py - name: Prepare schema validator comment if: failure() run: | From 0fec12c753bc4a094e89b0f7e809bf4b7dee7346 Mon Sep 17 00:00:00 2001 From: ugur Date: Mon, 20 May 2024 17:18:19 +0100 Subject: [PATCH 17/18] Added schema file --- .../config/dumps/neo4j2owl_config_schema.json | 95 +++++++++++++++++++ 1 file changed, 95 insertions(+) create mode 100644 cl_kb_pipeline/config/dumps/neo4j2owl_config_schema.json diff --git a/cl_kb_pipeline/config/dumps/neo4j2owl_config_schema.json b/cl_kb_pipeline/config/dumps/neo4j2owl_config_schema.json new file mode 100644 index 0000000..496436e --- /dev/null +++ b/cl_kb_pipeline/config/dumps/neo4j2owl_config_schema.json @@ -0,0 +1,95 @@ +{ + "$schema": "http://json-schema.org/draft-04/schema#", + "title": "neo4j2owl-config schema", + "description": "A JSON schema for documenting and validating the neo4j2owl configuration YAML.", + "name": "neo4j2owl_config_schema", + "type": "object", + "additionalProperties": false, + "definitions": { + "semantic_tag": { + "type": "object", + "additionalProperties": false, + "description": "Specifies a set of Manchester syntax class expressions and a label. Annotates all entities that are equivalent_to or subclasses of these expression with the label using the AP: {TBA} . In conversion to Neo4J these become neo4j:labels", + "properties": { + "classes": { + "type": "array", + "items": { + "type": "string" + }, + "description": "A list of Manchester syntax class expressions in which OWL entities are expressed as CURIEs." + }, + "label": { + "description": "Semantic tag name", + "type": "string" + }, + "description": { + "description": "Short description to give general information about the semantic tag, and state its purpose", + "type": "string" + } + }, + "required": [ "classes", "label"] + } + }, + "properties": { + "allow_entities_without_labels": { + "description": "Allow loading of entities without rdfs:label", + "type": "boolean" + }, + "index": { + "description": "?", + "type": "boolean" + }, + "testmode": { + "description": "?", + "type": "boolean" + }, + "batch": { + "description": "Create and load CSVs in batches (?)", + "type": "boolean" + }, + "batch_size": { + "description": "Size of batches to load", + "type": "integer" + }, + "safe_label": { + "description": "?", + "type": "string", + "enum": [ + "loose" + ] + }, + "relation_type_threshold": { + "description": "neo2owl attempts to consistently cast annotation value types (property value types). To do this it uses the threshold set here (more details TBA).", + "type": "number" + }, + "represent_values_and_annotations_as_json": { + "description": "Use this to record the IRIs of annotation properties whose values should be recorded as JSON, allowing the representation of axiom annotations on annotation axioms.", + "type": "object", + "additionalProperties": false, + "properties": { + "iris": { + "type": "array", + "items": { + "type": "string" + } + } + } + }, + "neo_node_labelling": { + "type": "array", + "items": { + "$ref": "#/definitions/semantic_tag" + } + }, + "curie_map": { + "description": "A map of prefixes to base IRIs.", + "type": "object", + "comment": "This could be improved." + }, + "filters":{ + "description": "", + "comment": "placeholder", + "type": "object" + } + } +} \ No newline at end of file From e2e6f65fed271ecac4771b169be104b6bfe1ced7 Mon Sep 17 00:00:00 2001 From: ugur Date: Tue, 21 May 2024 12:24:05 +0100 Subject: [PATCH 18/18] Updated permissions in schema_validator.yaml --- .github/workflows/schema_validator.yaml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.github/workflows/schema_validator.yaml b/.github/workflows/schema_validator.yaml index 4d7de31..aae6ecf 100644 --- a/.github/workflows/schema_validator.yaml +++ b/.github/workflows/schema_validator.yaml @@ -5,6 +5,8 @@ on: branches: [ main ] paths: - 'cl_kb_pipeline/config/dumps/neo4j2owl-config.yaml' +permissions: + pull-requests: write jobs: yaml-schema-validation: