A Geometric Perspective on the Power of Principal Component Association Tests in Multiple Phenotype Studies

DOI10.1080/01621459.2018.1513363zbMath1428.62475arXiv1710.10383OpenAlexW2963607751WikidataQ90352921 ScholiaQ90352921MaRDI QIDQ5242443

Xihong Lin, Zhong-Hua Liu

Publication date: 12 November 2019

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1710.10383

zbMATH Keywords

dimension reductionsummary statisticsprincipal anglepower analysisomnibus testgenome-wide association studies (GWAS)

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items

Sparse block signal detection and identification for shared cross-trait association analysis, A comparison of principal component methods between multiple phenotype regression and multiple SNP regression in genetic association studies, MPAT, Analyzing multiple phenotypes based on principal component analysis

Uses Software

• R
• mvtnorm
• PLINK
• TATES
• AS 155
• QSIMVN
• GWAS Catalog

Cites Work

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