Docker container with all the dependencies to run ClinVAP
939

Clinical Variant Annotation Pipeline.
The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.
i. Install nextflow
ii. Install one of docker, singularity or conda
iii. Download the pipeline and test it on a minimal dataset with a single command
nextflow run nf-core/clinvap -profile test,<docker/singularity/conda/institute>
Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use
-profile institutein your command. This will enable eitherdockerorsingularityand set the appropriate execution settings for your local compute environment.
iv. Start running your own analysis!
nextflow run nf-core/clinvap -profile <docker/singularity/conda/institute> --reads '*_R{1,2}.fastq.gz' --genome GRCh37
See usage docs for all of the available options when running the pipeline.
The nf-core/clinvap pipeline comes with documentation about the pipeline, found in the docs/ directory:
nf-core/clinvap was originally written by Bilge Sürün.
If you would like to contribute to this pipeline, please see the contributing guidelines.
For further information or help, don't hesitate to get in touch on Slack (you can join with this invite).
You can cite the nf-core pre-print as follows:
Ewels PA, Peltzer A, Fillinger S, Alneberg JA, Patel H, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. nf-core: Community curated bioinformatics pipelines. bioRxiv. 2019. p. 610741. doi: 10.1101/610741.
Content type
Image
Digest
Size
758.2 MB
Last updated
over 6 years ago
docker pull qbicpipelines/clinvap