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Bibliografiset tiedot
Päätekijä: broadinstitute
Aineistotyyppi: Recurso digital
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Julkaistu: Zenodo 2025
Linkit:https://doi.org/10.5281/zenodo.15537009
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author broadinstitute
author_facet broadinstitute
contents <h3>WDL Analysis Research Pipelines</h3> <p>The WDL 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>
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publishDate 2025
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record_format zenodo
spellingShingle github.com/broadinstitute/warp/run_ancestry
broadinstitute
<h3>WDL Analysis Research Pipelines</h3> <p>The WDL 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/run_ancestry
url https://doi.org/10.5281/zenodo.15537009