Marie Hannaert\ Centrum Medical Genetics Antwerp
This pipeline will process the files after deep WES, to see if there are any mutations in the somatic cells. It will at the end of the pipeline use multiple specific variant callers for somatic variants, compare these results and make a consensus of these results.
Snakemake is a workflow management system that helps Snakemake is a workflow management system that helps create and execute data processing pipelines. It requires Python 3 and can be easily installed via the Bioconda package.
Look at the conda documentation for installing this. Conda You will also need Biconda. Bioconda
Use the snakemake documentation for installing Snakemake als a conda package. Snakemake
You can download the pipeline from github. This will include: Snakefile, scripts and the needed enviroment, to your local machine. It's good practice to create a Snakemake/ directory to collect all your pipelines. Download the TAA somatic pipeline into your Snakemake directory using:
$ cd Snakemake/
$ git clone https://github.com/MarieHannaert/TAA_somatic_snakemake.git
You can install the enviroment by using the TAA_somatic_pipeline.yaml in the envs directory.
$ cd TAA_somatic_snakemake/
$ conda enc create -f envs/TAA_somatic_pipeline.yaml
Before you can run the pipeline you need to prepare some steps.
First activate the conda enviroment by running the following command:
$ conda activate TAA_somatic_pipeline
Normally infront of your promt the enviroment will appear.
Go to the directory:
$ cd TAA_somatic_snakemake/
Secondly you need to place the samples you want to analyse in the data directory this can be done with the following command:
$ ln <path to your samples> data/
Now you are ready to run the pipeline.
In the directory you can run the pipeline in different ways. With slurm you need a .config/snakemake/slurm/config.yaml, this file contains information on how snakemake may use the resources. More information can be found in the documentation of snakemake Snakemake_slurm. If you have this you can run the pipeline with the following command in the pipeline directory:
$ snakemake --profile ../.config/snakemake/slurm --verbose --rerun-incomplete --latency-wait 36000
If you are running without slurm (which is not advisable) the following command is used:
$ snakemake -p --cores $(nproc) --verbose --rerun-incomplete --latency-wait 36000
