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第一著者: broadinstitute
フォーマット: Recurso digital
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出版事項: Zenodo 2026
オンライン・アクセス:https://doi.org/10.5281/zenodo.20220170
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author broadinstitute
author_facet broadinstitute
contents <h3>Warp Analysis Research Pipelines</h3> <p>The Warp Analysis Research Pipelines (WARP) repository is a collection of cloud-optimized pipelines for processing biological data from the Broad Institute Data Sciences Platform and collaborators.</p> <p>WARP provides robust, standardized data analysis for the Broad Institute Genomics Platform and large consortia like the Human Cell Atlas and the BRAIN Initiative. WARP pipelines are rigorously scientifically validated, high scale, reproducible and open source, released under the <a href="https://github.com/broadinstitute/warp/blob/master/LICENSE">BSD 3-Clause license</a>.</p> <h3>Pipeline releases</h3> <p>All pipeline releases are listed on the WARP <a href="https://github.com/broadinstitute/warp/releases">releases page</a>. To discover and search releases, use the WARP command-line tool <a href="https://github.com/broadinstitute/warp/tree/develop/wreleaser">Wreleaser</a>.</p> <h3>WARP Dockers and custom tools in warp-tools repository</h3> <p>All Dockers and custom tools used for WARP's WDL Workflows are maintained in a separate repository, <a href="https://github.com/broadinstitute/warp-tools">warp-tools</a>.</p> <h3>WARP documentation</h3> <p>Read more about our pipelines and repository on the <a href="https://broadinstitute.github.io/warp/">WARP documentation site</a>.</p> <p>To contribute to WARP, please read the <a href="https://broadinstitute.github.io/warp/docs/contribution/README">contribution guidelines</a>.</p> <h3>Citing WARP</h3> <p>When citing WARP, please use the following:</p> <p>Degatano, K.; Awdeh, A.; Dingman, W.; Grant, G.; Khajouei, F.; Kiernan, E.; Konwar, K.; Mathews, K.; Palis, K.; Petrillo, N.; Van der Auwera, G.; Wang, C.; Way, J.; Pipelines, W. WDL Analysis Research Pipelines: Cloud-Optimized Workflows for Biological Data Processing and Reproducible Analysis. Preprints 2024, 2024012131. https://doi.org/10.20944/preprints202401.2131.v1</p> <p><a href="https://github.com/broadinstitute/warp/actions?query=workflow%3A%22Deploy+WARP+Website%22"></a></p>
format Recurso digital
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institution Zenodo
language
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle github.com/broadinstitute/warp/get_wgs_median_coverage
broadinstitute
<h3>Warp Analysis Research Pipelines</h3> <p>The Warp Analysis Research Pipelines (WARP) repository is a collection of cloud-optimized pipelines for processing biological data from the Broad Institute Data Sciences Platform and collaborators.</p> <p>WARP provides robust, standardized data analysis for the Broad Institute Genomics Platform and large consortia like the Human Cell Atlas and the BRAIN Initiative. WARP pipelines are rigorously scientifically validated, high scale, reproducible and open source, released under the <a href="https://github.com/broadinstitute/warp/blob/master/LICENSE">BSD 3-Clause license</a>.</p> <h3>Pipeline releases</h3> <p>All pipeline releases are listed on the WARP <a href="https://github.com/broadinstitute/warp/releases">releases page</a>. To discover and search releases, use the WARP command-line tool <a href="https://github.com/broadinstitute/warp/tree/develop/wreleaser">Wreleaser</a>.</p> <h3>WARP Dockers and custom tools in warp-tools repository</h3> <p>All Dockers and custom tools used for WARP's WDL Workflows are maintained in a separate repository, <a href="https://github.com/broadinstitute/warp-tools">warp-tools</a>.</p> <h3>WARP documentation</h3> <p>Read more about our pipelines and repository on the <a href="https://broadinstitute.github.io/warp/">WARP documentation site</a>.</p> <p>To contribute to WARP, please read the <a href="https://broadinstitute.github.io/warp/docs/contribution/README">contribution guidelines</a>.</p> <h3>Citing WARP</h3> <p>When citing WARP, please use the following:</p> <p>Degatano, K.; Awdeh, A.; Dingman, W.; Grant, G.; Khajouei, F.; Kiernan, E.; Konwar, K.; Mathews, K.; Palis, K.; Petrillo, N.; Van der Auwera, G.; Wang, C.; Way, J.; Pipelines, W. WDL Analysis Research Pipelines: Cloud-Optimized Workflows for Biological Data Processing and Reproducible Analysis. Preprints 2024, 2024012131. https://doi.org/10.20944/preprints202401.2131.v1</p> <p><a href="https://github.com/broadinstitute/warp/actions?query=workflow%3A%22Deploy+WARP+Website%22"></a></p>
title github.com/broadinstitute/warp/get_wgs_median_coverage
url https://doi.org/10.5281/zenodo.20220170