STAAR工作流程：一种用于可扩展和可重复的罕见变异分析的基于云的工作流程。
STAAR workflow: a cloud-based workflow for scalable and reproducible rare variant analysis.
作者信息
Gaynor Sheila M, Westerman Kenneth E, Ackovic Lea L, Li Xihao, Li Zilin, Manning Alisa K, Philippakis Anthony, Lin Xihong
机构信息
Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA 02115, USA.
Department of Medicine, Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA 02114, USA.
出版信息
Bioinformatics. 2022 May 26;38(11):3116-3117. doi: 10.1093/bioinformatics/btac272.
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.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
摘要
我们开发了使用注释信息进行关联分析的变异集测试（STAAR）工作流描述语言（WDL）工作流，以促进全基因组测序关联研究中罕见变异的分析。用WDL编写的开放获取的STAAR工作流允许用户对以基因为中心和遗传区域方法进行罕见变异测试，实现全基因组、候选和条件分析。它将功能注释纳入工作流，如STAAR方法中所介绍的，以提高罕见变异分析能力。该工具经过专门开发和优化，可在基于云的平台（如由Terra提供支持的BioData Catalyst）上实施。它为罕见变异分析提供了易于使用的功能，可纳入详尽的全基因组测序分析流程。
可用性和实施
该工作流可从https://dockstore.org/workflows/github.com/sheilagaynor/STAAR_workflow免费获取。
补充信息
补充数据可在《生物信息学》在线获取。
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