Computationally efficient, exact, covariate-adjusted genetic principal component analysis by leveraging individual marker summary statistics from large biobanks-Reference-Cited by-同舟云学术

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Computationally efficient, exact, covariate-adjusted genetic principal component analysis by leveraging individual marker summary statistics from large biobanks

Published:2019-11-27 Issue: Volume: Page:
ISSN:
Container-title:Biocomputing 2020
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Author:

Wolf Jack M.¹,Barnard Martha¹,Xia Xueting²,Ryder Nathan³,Westra Jason⁴,Tintle Nathan¹

Affiliation:

1. Department of Mathematics, Statistics, and Computer Science, St. Olaf College, Northfield, MN 55057, USA

2. Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409, USA

3. Department of Statistics, Colorado State University, Fort Collins, CO 80523, USA

4. Department of Math, Computer Science, and Statistics, Dordt University, Sioux Center, IA 51250, USA

Publisher

WORLD SCIENTIFIC

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. pcsstools: Tools for Regression Using Pre-Computed Summary Statistics;CRAN: Contributed Packages;2021-03-23

2. Using summary statistics to evaluate the genetic architecture of multiplicative combinations of initially analyzed phenotypes with a flexible choice of covariates;2021-03-09

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