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Article

Maximizing the power of principal-component analysis of correlated phenotypes in genome-wide association studies.

American journal of human genetics - 1 May 2014

Aschard Hugues, Vilhjálmsson Bjarni J, Greliche Nicolas, Morange Pierre-Emmanuel, Trégouët David-Alexandre, Kraft Peter

Abstract excerpt

Many human traits are highly correlated. This correlation can be leveraged to improve the power of genetic association tests to identify markers associated with one or more of the traits. Principal component analysis (PCA) is a useful tool that has been widely used for the multivariate analysis of correlated variables. PCA is usually applied as a dimension reduction method: the few top principal components (PCs)...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 24746957
DOI: 10.1016/j.ajhg.2014.03.016
PMCID: PMC4067564

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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