Robust inference of population structure for ancestry prediction and correction of stratification in the presence of relatedness.

ABSTRACT: Population structure inference with genetic data has been motivated by a variety of applications in population genetics and genetic association studies. Several approaches have been proposed for the identification of genetic ancestry differences in samples where study participants are assumed to be unrelated, including principal components analysis (PCA), multidimensional scaling (MDS), and model-based methods for proportional ancestry estimation. Many genetic studies, however, include individuals with some degree of relatedness, and existing methods for inferring genetic ancestry fail in related samples. We present a method, PC-AiR, for robust population structure inference in the presence of known or cryptic relatedness. PC-AiR utilizes genome-screen data and an efficient algorithm to id

SUBMITTER: Conomos MP 

PROVIDER: S-EPMC4836868 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature