STAAR workflow: a cloud-based workflow for scalable and reproducible rare variant analysis
dc.contributor.author | Gaynor, Sheila M. | |
dc.contributor.author | Westerman, Kenneth E. | |
dc.contributor.author | Ackovic, Lea L. | |
dc.contributor.author | Li, Xihao | |
dc.contributor.author | Li, Zilin | |
dc.contributor.author | Manning, Alisa K. | |
dc.contributor.author | Philippakis, Anthony | |
dc.contributor.author | Lin, Xihong | |
dc.contributor.department | Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health | |
dc.date.accessioned | 2024-09-25T09:56:23Z | |
dc.date.available | 2024-09-25T09:56:23Z | |
dc.date.issued | 2022 | |
dc.description.abstract | Summary: We developed the variant-Set Test for Association using Annotation infoRmation (STAAR) workflow description language (WDL) workflow to facilitate the analysis of rare variants in whole genome sequencing association studies. The open-access STAAR workflow written in the WDL allows a user to perform rare variant testing for both gene-centric and genetic region approaches, enabling genome-wide, candidate and conditional analyses. It incorporates functional annotations into the workflow as introduced in the STAAR method in order to boost the rare variant analysis power. This tool was specifically developed and optimized to be implemented on cloud-based platforms such as BioData Catalyst Powered by Terra. It provides easy-to-use functionality for rare variant analysis that can be incorporated into an exhaustive whole genome sequencing analysis pipeline. Availability and implementation: The workflow is freely available from https://dockstore.org/workflows/github.com/sheilagaynor/STAAR_workflow. | |
dc.eprint.version | Final published version | |
dc.identifier.citation | Gaynor SM, Westerman KE, Ackovic LL, et al. STAAR workflow: a cloud-based workflow for scalable and reproducible rare variant analysis. Bioinformatics. 2022;38(11):3116-3117. doi:10.1093/bioinformatics/btac272 | |
dc.identifier.uri | https://hdl.handle.net/1805/43584 | |
dc.language.iso | en_US | |
dc.publisher | Oxford University Press | |
dc.relation.isversionof | 10.1093/bioinformatics/btac272 | |
dc.relation.journal | Bioinformatics | |
dc.rights | Publisher Policy | |
dc.source | PMC | |
dc.subject | Cloud computing | |
dc.subject | Genome-wide association study | |
dc.subject | Software | |
dc.subject | Workflow | |
dc.title | STAAR workflow: a cloud-based workflow for scalable and reproducible rare variant analysis | |
dc.type | Article | |
ul.alternative.fulltext | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9991895/ |