Bulk RNAseq Workflow

Table of Contents

• 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
  • Troubleshooting
  • Citing

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

    • iSEE
      1. Deployment of iSEE to shinyapps.io can be enabled/disabled using deploy_to_shinyio. If set to False, the following steps can be ignored.
      2. iSEE_app_name should be a new app name that does not already exist in your shinyapps.io account. Otherwise, the deployment will fail or your old app may be overwritten.
      3. In R, run rsconnect::accounts(). Choose one of the values in the 'name' column to fill in shinyio_account_name. If rsconnect::accounts() does not return any results, you need to first follow the instructions here to set up your shinyapps.io credentials.

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

Troubleshooting

• If running the workflow on an older version of R, incompatibilities with the latest CRAN packages can occur if an older version of the CRAN package is not available in the renv cache or in the user library. To install an older version of a CRAN package, replace/add the package name in the config/R_proj_packages.txt file with package_name@version_number. The version number should be as listed in the package's reference manual e.g. [email protected]. Note that this version number is only considered if the workflow was unable to copy from the cache or user library.

Citing

If you use this workflow, please cite our Zenodo DOI in your publication(s) in addition to the tools used by this workflow.