Bulk RNAseq Workflow

• Bulk RNAseq Workflow
  • Usage
    • Step 1: Configure the workflow
    • Step 1b (optional): Specify contig groups for variant calling
    • Step 2: Test and run the workflow

Usage

NOTE this workflow is optimized for the HPC @ Van Andel Institute.

Step 1: Configure the workflow

• Move your sequencing reads to raw_data/

• Modify the config, comparisons, and samplesheet:

  • config/samplesheet/units.tsv; To make a template based in the files in raw_data/, run ./make_units_template.sh.

    • sample - ID of biological sample; Must be unique.
    • group - Experimental group
    • fq1 - name of read1 fastq
    • fq2 - name of read2 fastq
    • RG - space-delimited read group specification e.g. ID:XYZ PU:XYZ LB:LIB01 PL:ILLUMINA SM:SAMPLE01

  • config/samplesheet/comparisons.tsv; fill this out with you

    • comparison_name - Name of your comparison (use only letters, numbers, and underscores -- special characters or spaces will result in errors).
    • group_test - Experimental group (treated/condition/phenotype)
    • group_reference - Reference group (control/wildtype/baseline)

  • config/config.yaml

Step 1b (optional): Specify contig groups for variant calling

Certain parts of the variant calling will parallelize by splitting by contig. The non-standard chromosomes can be grouped together since they are usually very small. The contig groupings are specified by the file config/grouped_contigs.tsv; column 1 is the name for the group of contigs and column 2 is a comma-separated list of the contigs.

cd config
module load bbc2/R/alt/R-4.2.1-setR_LIBS_USER
Rscript --vanilla group_chroms.R 

Step 2: Test and run the workflow

Test your configuration by performing a dry-run via

snakemake -npr

Execute from within your project directory as a SLURM job.

sbatch bin/run_snake.sh