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

ABSTRACT: Joint analysis of multiple phenotypes can increase statistical power in genetic association studies. Principal component analysis, as a popular dimension reduction method, especially when the number of phenotypes is high-dimensional, has been proposed to analyze multiple correlated phenotypes. It has been empirically observed that the first PC, which summarizes the largest amount of variance, can be less powerful than higher order PCs and other commonly used methods in detecting genetic association signals. In this paper, we investigate the properties of PCA-based multiple phenotype analysis from a geometric perspective by introducing a novel concept called principal angle. A particular PC is powerful if its principal angle is 0° and is powerless if its principal angle is 90°. Without prio

SUBMITTER: Liu Z 

PROVIDER: S-EPMC6764517 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature