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STAAR Workflow: A cloud-based workflow for scalable and reproducible rare variant analysis

Sheila M. Gaynor, Kenneth E. Westerman, Lea L. Ackovic, Xihao Li, Zilin Li, Alisa K. Manning, Anthony Philippakis, Xihong Lin
doi: https://doi.org/10.1101/2021.09.07.456116
Sheila M. Gaynor
1Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, 02115, USA
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Kenneth E. Westerman
2The Broad Institute of MIT and Harvard, Cambridge, MA, 02124, USA
3Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, 02114, USA
4Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
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Lea L. Ackovic
5Seven Bridges, Charlestown, MA 02129, USA
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Xihao Li
1Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, 02115, USA
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Zilin Li
1Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, 02115, USA
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Alisa K. Manning
2The Broad Institute of MIT and Harvard, Cambridge, MA, 02124, USA
3Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, 02114, USA
4Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
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Anthony Philippakis
2The Broad Institute of MIT and Harvard, Cambridge, MA, 02124, USA
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Xihong Lin
1Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, 02115, USA
6Department of Statistics, Harvard University, Cambridge, 02138, USA
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  • For correspondence: xlin@hsph.harvard.edu
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Abstract

Summary We developed the STAAR WDL workflow to facilitate the analysis of rare variants in whole genome sequencing association studies. The open-access STAAR workflow written in the workflow description language (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.

Competing Interest Statement

AAP is a Venture Partner at GV, and makes investments in life sciences and data sciences companies. He has also received funding from Intel, Microsoft, Alphabet, IBM, Rakuten, Bayer, and Novartis.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted September 08, 2021.
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STAAR Workflow: A cloud-based workflow for scalable and reproducible rare variant analysis
Sheila M. Gaynor, Kenneth E. Westerman, Lea L. Ackovic, Xihao Li, Zilin Li, Alisa K. Manning, Anthony Philippakis, Xihong Lin
bioRxiv 2021.09.07.456116; doi: https://doi.org/10.1101/2021.09.07.456116
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STAAR Workflow: A cloud-based workflow for scalable and reproducible rare variant analysis
Sheila M. Gaynor, Kenneth E. Westerman, Lea L. Ackovic, Xihao Li, Zilin Li, Alisa K. Manning, Anthony Philippakis, Xihong Lin
bioRxiv 2021.09.07.456116; doi: https://doi.org/10.1101/2021.09.07.456116

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