iclip-seq-snakemake

Snakemake based pipeline for analysing iCLIP-Seq data

To Run

In order to make full use of the pipeline, it should be run on cluster. It submits independent qsub job for all steps which are independent. If there are 3 replicates the pipeline will run paralley for all 3, using 3 qsub jobs.

Step 1

Install dependencies:

conda env create -n clipseq -f environment.yml

Step 2a

Edit config.py. All the variables in the file are self explanatory.

The SAMPLES variable refers to the filename of fastqs leaving out the extension which is assumed to be .fq.

SRC_DIR: Path to the scripts/ directory(absolute)

RAWDATA_DIR: Where should the fasts be read fromi.(ROOT_DIR is redundant)

STAR_INDEX: Directory location of STAR index

_BED: Location to BED files, required for annotation

The _OTHER fields are relevant only if you have data from some 'other' species. For example, if you have human and mouse iCLIP data, these fields are used to do a lot of liftover operations. If you have single specie data, you can leave the _OTHER fields as they are.

Step 2b

Edit jobscript.sh so that it has the correct PATH variable. Make sure it includes the conda environment as the first. In my case it is home/cmb-panasas2/skchoudh/software_frozen/anaconda2/envs/clipseq/bin. The reason to do this hard coding of PATH is because some hpc nodes fail to run the job because they can't detect the environment often.

Step 3

On hpc-cmb login node:

bash submitall.sh

Error log will be printed on STDOUT indicating if jobs are running or not.