Merge pull request #197 from wilhelm-lab/release/0.6.0

Release/0.6.0

.cookietemple.yml

@@ -15,5 +15,5 @@ full_name: Victor Giurcoiu
 email: [email protected]
 project_name: oktoberfest
 project_short_description: Public repo oktoberfest
-version: 0.5.3
+version: 0.6.0
 license: MIT

.flake8

@@ -7,6 +7,6 @@ docstring-convention = google
 per-file-ignores =
 	tests/*:S101
 	**/__init__.py:F401,F403
-    docs/conf.py:S404,S607,S603
-	oktoberfest/preprocessing/preprocessing.py:S301
+    	docs/conf.py:S404,S607,S603
+	oktoberfest/runner.py:S301,S403
 docstring_style = sphinx

.github/release-drafter.yml

@@ -1,5 +1,5 @@
-name-template: "0.5.3 🌈" # <<COOKIETEMPLE_FORCE_BUMP>>
-tag-template: 0.5.3 # <<COOKIETEMPLE_FORCE_BUMP>>
+name-template: "0.6.0 🌈" # <<COOKIETEMPLE_FORCE_BUMP>>
+tag-template: 0.6.0 # <<COOKIETEMPLE_FORCE_BUMP>>
 exclude-labels:
     - "skip-changelog"
 

Dockerfile

@@ -17,7 +17,7 @@ RUN apt-get update && apt-get install -y \
 ENV HOME /root
 WORKDIR /root
 
-RUN pip install poetry==1.3.2
+RUN pip install poetry==1.6.1
 # poetry useses virtualenvs by default -> we want global installation
 RUN poetry config virtualenvs.create false
 ADD pyproject.toml /root/pyproject.toml

ReadMe.md

@@ -20,10 +20,20 @@ The official Oktoberfest documentation can be found at https://oktoberfest.readt
 
 Please always cite the main publication:
 
-[Oktoberfest] Picciani M, Gabriel W, Giurcoiu VG, Shouman O, Hamood F, Lautenbacher L, Jensen CB, Müller J, Kalhor M, Soleymaniniya A, Kuster B, The M, Wilhelm M (2023), _Oktoberfest: Open-source spectral library generation and rescoring pipeline based on Prosit_, [Proteomics](https://doi.org/10.1002/pmic.202300112)
+[Oktoberfest] Picciani M, Gabriel W, Giurcoiu VG et al. (2023), _Oktoberfest: Open-source spectral library generation and rescoring pipeline based on Prosit_, [Proteomics](https://doi.org/10.1002/pmic.202300112)
 
-Should you make use of peptide property predictions through Oktoberfest using one of the supported Prosit models, please also cite one of the following:
+Should you make use of peptide property predictions through Oktoberfest using one of the supported Prosit models, please also cite the following:
 
-[Prosit] Gessulat S, Schmidt T, Zolg DP, Samaras P, Schnatbaum K, Zerweck J, Knaute T, Rechenberger J, Delanghe B, Huhmer A, Reimer U, Ehrlich HC, Aiche S, Kuster B, Wilhelm M (2019), _TriMap: PROSIT: Proteome-wide prediction of peptide tandem mass spectra by deep learning_, [Nature Methods](https://doi.org/10.1038/s41592-019-0426-7)
+When using Prosit
 
-[Prosit-TMT] Gabriel W, The M, Zolg D, Bayer FP, Shouman O, Lautenbacher L, Schnatbaum K, Zerweck J, Knaute T, Delanghe B, Huhmer A, Wenschuh H, Reimer U, Médard G, Kuster B, Wilhelm M (2022), _TriMap: Prosit-TMT: Deep Learning Boosts Identification of TMT-Labeled Peptides_, [Analytical Chemistry](https://doi.org/10.1021/acs.analchem.1c05435)
+[Prosit] Gessulat S, Schmidt T, Zolg DP et al. (2019), _PROSIT: Proteome-wide prediction of peptide tandem mass spectra by deep learning_, [Nature Methods](https://doi.org/10.1038/s41592-019-0426-7)
+
+[Prosit-HLA] Wilhelm M, Zolg DP, Graber M et al. (2021), _Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics_, [Nature Communications](https://doi.org/10.1038/s41467-021-23713-9)
+
+When using Prosit-TMT
+
+[Prosit-TMT] Gabriel W, The M, Zolg D et al. (2022), _TriMap: Prosit-TMT: Deep Learning Boosts Identification of TMT-Labeled Peptides_, [Analytical Chemistry](https://doi.org/10.1021/acs.analchem.1c05435)
+
+When using Prosit-timsTOF
+
+[Prosit-timsTOF] Adams C, Gabriel W, Laukens K et al. (2023), _Fragment ion intensity prediction improves the identification rate of non-tryptic peptides in timsTOF_, [BioRxiv](https://doi.org/10.1101/2023.07.17.549401)

cookietemple.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.5.3
+current_version = 0.6.0
 
 [bumpversion_files_whitelisted]
 init_file = oktoberfest/__init__.py

docs/API.rst

@@ -25,6 +25,7 @@ Generating libraries
    :toctree: api/pp
 
    pp.digest
+   pp.generate_metadata
    pp.gen_lib
    pp.merge_spectra_and_peptides
    pp.annotate_spectral_library
@@ -35,7 +36,8 @@ Spectra preprocessing
    :toctree: api/pp
 
    pp.list_spectra
-   pp.convert_spectra_to_mzml
+   pp.convert_raw_to_mzml
+   pp.convert_d_to_hdf
    pp.load_spectra
 
 
@@ -46,6 +48,9 @@ Peptide preprocessing
 
    pp.convert_search
    pp.load_search
+   pp.split_search
+   pp.convert_timstof_metadata
+   pp.split_timstof_metadata
    pp.filter_peptides
    pp.filter_peptides_for_model
 

docs/_static/custom_cookietemple.css

@@ -35,6 +35,11 @@ table.align-default {
     margin-left: 0;
 }
 
+.wy-table-responsive table th p,
+.wy-table-responsive table td p {
+    white-space: normal;
+}
+
 .autosummary {
     margin-left: 0 !important;
 }
@@ -58,6 +63,10 @@ table.align-default {
     padding-left: 50px;
 }
 
+.lib-config-table tbody tr:nth-last-child(-n + 6) td:nth-child(1) {
+    padding-left: 50px;
+}
+
 .digest-config-table tbody tr:not(:first-child) td:nth-child(1) {
     padding-left: 50px;
 }

docs/conf.py

@@ -54,9 +54,9 @@
 # the built documents.
 #
 # The short X.Y version.
-version = "0.5.3"
+version = "0.6.0"
 # The full version, including alpha/beta/rc tags.
-release = "0.5.3"
+release = "0.6.0"
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.