Automated workflow for small RNA sequence data

Snakemake workflow for processing small RNA-seq libaries produced by Illumina small sequencing kits.

Requirments

• demultiplex fastq files in located in data directory. They need to be in the form {sample}_R1.fastq.gz

• Snakefile shipped with this repository.

• config.yaml shipped with this repository. It contains all parameters and settings to customize the processing of the current dataset.

• samples.csv listing all samples in the data directory withoug the _R1.fastq.gz suffix. The first line is the header i.e. the work library. An example is shipped with this repository which can be used as a template.

• Optionall: environment.yaml to create the software environment if conda is used.

• Installation of snakemake and optionally conda

• If conda is not used, bowtie, fastqc, samtools and deeptools need to be in the PATH.

  The above files can be downloaded as a whole by cloning the repository (which requires git):

git clone https://github.com/seb-mueller/snakemake_sRNAseq.git

Or individually for example the Snakemake file using wget:

wget https://raw.githubusercontent.com/seb-mueller/snakemake_sRNAseq/master/Snakefile

creating conda environment

conda env create --file environment.yaml --name srna_mapping

activate

conda activate srna_mapping

To deactivate the environment, run:

conda deactivate

Update:

git pull
conda env update --file environment.yaml --name srna_mapping

Usage:

Navigate in a Unix shell to the base directory contains the files listed above plus the data directory including the data like int this example:

.
├── data
│   ├── test2_R1.fastq.gz
│   └── test3_R1.fastq.gz
├── config.yaml
├── environment.yaml
├── samples.csv
└── Snakefile

Then just run snakmake in base directory:

# the most basic usage
snakemake
# recommended: automatic conda managment in central location
snakemake --use-conda --conda-prefix ~/.myconda -p

useful parameters:

• --cores max number of threads
• -n dryrun
• -p print commands
• --use-conda
• --conda-prefix ~/.myconda
• --forcerun postmapping forces rerun of a given rule (e.g. postmapping)
• --keep-going if for example one sample fails, pipeline will still try to process other samples

Output:

trimmed, log and mapped directory with trimming and mapping results.

Update: added STAR support

# create star index (goes in staridx folder)
snakemake -p --skip-script-cleanup staridx --cores 3
# then map using star
snakemake -p --skip-script-cleanup starmap --cores 3
# TODO: create bw files form STAR mapping