advanced

Warning: the documentation on this wiki is deprecated and refers to V-pipe versions 1.0 and 2.0 (published in Bioinformatics). You can find the most recent documentation on running V-pipe 3.0 in the usage section of readme on the master branch.

Running V-pipe

One can produce intermediate results, by explicitly setting the target rule. For example, to obtain trimmed reads use the following:

./vpipe alltrimmed

Particularly, you can check the number of reads retain after the quality assurance and adjust the astringency of this step.

To obtain minor allele frequencies use the following:

./vpipe minor_variants 

To obtain FASTQC reports use the following:

./vpipe allfastqc

To clean previously produced results, we provide a series a clean commands, e.g.,

./vpipe extractclean
./vpipe trimmingclean
./vpipe vicunaclean
./vpipe msaclean
./vpipe alignclean
./vpipe bwaclean
./vpipe bowtieclean
./vpipe snvclean
./vpipe haplocliqueclean
./vpipe savageclean

NOTE Starting Snakemake 5.11.0 the --cores option is mandatory. Depending on the Snakemake version you are using, you might have to specify the number of cores.

Running V-pipe on a LSF cluster

For most applications, running V-pipe on a local machine may not be efficient. When running V-pipe on a cluster, every rule is executed as an independent job, but each job is scheduled only after its input files become available. To schedule jobs on a LSF cluster, you can run V-pipe using option --cluster, e.g

bsub ./vpipe --cluster "bsub -M {params.mem} -n {threads} -W {params.time} -R \"rusage [mem={params.mem},scratch={params.scratch}]\" -e {log.errfile} -o {log.outfile}" -j 100 --use-conda -p

Using this command, at most 100 jobs will be launched (option -j) and resources (e.g memory, time and threads) will be requested as indicated under the directive params for each rule. In addition, by using option --use-conda, Conda environments specific for each rule will be created and all dependencies will be fetched from the specified channel.