Fast and robust ancestry prediction using principal component analysis.

ABSTRACT:

Motivation

Population stratification (PS) is a major confounder in genome-wide association studies (GWAS) and can lead to false-positive associations. To adjust for PS, principal component analysis (PCA)-based ancestry prediction has been widely used. Simple projection (SP) based on principal component loadings and the recently developed data augmentation, decomposition and Procrustes (ADP) transformation, such as LASER and TRACE, are popular methods for predicting PC scores. However, the predicted PC scores from SP can be biased toward NULL. On the other hand, ADP has a high computation cost because it requires running PCA separately for each study sample on the augmented dataset.

Results

We develop and propose two alternative approaches: bias-adjusted projection (AP) and o

SUBMITTER: Zhang D 

PROVIDER: S-EPMC7267814 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature