Article
Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies.
Nature genetics - 1 Jan 2023
Li Xihao, Quick Corbin, Zhou Hufeng, Gaynor Sheila M, Liu Yaowu, Chen Han, Selvaraj Margaret Sunitha, Sun Ryan, Dey Rounak, Arnett Donna K, Bielak Lawrence F, Bis Joshua C, Blangero John, Boerwinkle Eric, Bowden Donald W, Brody Jennifer A, Cade Brian E, Correa Adolfo, Cupples L Adrienne, Curran Joanne E, de Vries Paul S, Duggirala Ravindranath, Freedman Barry I, Göring Harald H H, Guo Xiuqing, Haessler Jeffrey, Kalyani Rita R, Kooperberg Charles, Kral Brian G, Lange Leslie A, Manichaikul Ani, Martin Lisa W, McGarvey Stephen T, Mitchell Braxton D, Montasser May E, Morrison Alanna C, Naseri Take, O'Connell Jeffrey R, Palmer Nicholette D, Peyser Patricia A, Psaty Bruce M, Raffield Laura M, Redline Susan, Reiner Alexander P, Reupena Muagututi'a Sefuiva, Rice Kenneth M, Rich Stephen S, Sitlani Colleen M, Smith Jennifer A, Taylor Kent D, Vasan Ramachandran S, Willer Cristen J, Wilson James G, Yanek Lisa R, Zhao Wei, Rotter Jerome I, Natarajan Pradeep, Peloso Gina M, Li Zilin, Lin Xihong
Abstract excerpt
Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework...
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