rnaseq-pipeline

Scripts for annotating 10x Genomics scRNA-seq analysis data

Contents

Dependencies

10x cellranger scRNA-seq data

Metadata Annotation: tenx_rna_metadata_update.R

• Parameters
• Guidelines
  • SampleSheet
  • Outputs

Dependencies

This repository requires that pandoc and libhdf5-dev libraries are installed:

sudo apt-get install pandoc libhdf5-dev

It also depends on the H5MANIPULATOR, jsonlite, rmarkdown, and optparse libraries.

jsonlite, rmarkdown and optparse are available from CRAN, and can be installed in R using:

install.packages("jsonlite")
install.packages("rmarkdown")
install.packages("optparse")

Sys.setenv(GITHUB_PAT = "[your_PAT_here]")
devtools::install_github("bwh-bioinformatics-hub/H5MANIPULATOR")

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Metadata annotation for cellranger results

This repository can add important QC characteristics and cell metadata for 10x Genomics. It requires the filtered_feature_bc_matrix.h5, molecule_info.h5, and metrics_summary.csv files generated by cellranger count as inputs, as well as a SampleSheet.csv file (as described below), and generates a decorated output .h5 file based on these parameters and a SampleID.

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There are 5 parameters for this script:

• -i or --in_h5: The path to the filtered_feature_bc_matrix.h5 file from cellranger outs/
• -l or --in_mol: The path to the molecule_info.h5 file from cellranger outs/
• -s or --in_sum: The path to the metrics_summary.csv file from cellranger outs/
• -k or --in_key: The path to SampleSheet.csv
• -j or --in_sample: Sample Name

An example run for a cellranger count result is:

Rscript --vanilla \
  tenx-rnaseq-pipeline/tenx_rna_metadata_update.R \
  -i outs/filtered_feature_bc_matrix.h5 \
  -l outs/molecule_info.h5 \
  -s outs/metrics_summary.csv \
  -k outs/SampleSheet.csv \
  -j Sample_Name \

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SampleSheet.csv formats and output filenames

SampleSheet.csv

It should have 3 columns: SampleID, Type (Control, Treatment), and LibraryID

SampleID,Type,LibraryID
CRCI1,Saline,CRN00234043
CRCI2,Saline,CRN00234044
CRCI3,Chemotherapy,CRN00234045

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output files

Outputs, two files will be generated. The .h5 will be named based on Library and SampleID, while the JSON metrics for this well will be named based on Library:

• .h5 file: [SampleID]_[Type].h5, e.g. CRCI1.h5
• JSON file: [LibraryID]_sample_metrics.json, e.g. CRCI1-Saline_sample_metrics.json

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