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cellranger_count.smk

Snakemake workflow for gene count quantification from single-cell/nucleus RNA-seq data by Cell Ranger.

Note

Please make sure that you have Singularity and Snakemake installed on your system and cloned the SnakeNgs repository.

Workflow

cellranger_count.smk rulegraph

The rulegraph was created by snakevision.

  1. Make aliases for the input FASTQ files and convert the file names to the 10x Genomics format (e.g., sample_S1_L001_R1_001.fastq.gz).
  2. Run cellranger count to quantify gene expression from the input FASTQ files.
  3. Make summary statistics using MultiQC.

Usage

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snakemake -s /path/to/SnakeNgs/snakefile/cellranger_count.smk \
--configfile /path/to/config.yaml \
--cores <int> \
--use-singularity \
--rerun-incomplete

config.yaml should contain the following information:

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workdir: /path/to/output
experiment_table: /path/to/experiment_table.tsv
transcriptome: /path/to/reference_transcriptome
create_bam: "false" # ["true", "false"]
  • experiment_table.tsv should contain the following information:
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sample  R1  R2
sample1 path/to/sample1_L001_R1.fastq.gz,path/to/sample1_L002_R1.fastq.gz path/to/sample1_L001_R2.fastq.gz,path/to/sample1_L002_R2.fastq.gz
sample2 path/to/sample2_L001_R1.fastq.gz,path/to/sample2_L002_R1.fastq.gz path/to/sample2_L001_R2.fastq.gz,path/to/sample2_L002_R2.fastq.gz
sample3 path/to/sample3_L001_R1.fastq.gz,path/to/sample3_L002_R1.fastq.gz path/to/sample3_L001_R2.fastq.gz,path/to/sample3_L002_R2.fastq.gz

R1 and R2 are comma-separated paths to the FASTQ files for read 1 and read 2, respectively.

  • reference_transcriptome should be the path to the reference transcriptome directory made by cellranger mkref.

  • create_bam should be either true or false. If true, the workflow will create BAM files from the CellRanger output.

Docker image used in the workflow