Adjusting for population stratification in a fine scale with principal components and sequencing data.

ABSTRACT: Population stratification is of primary interest in genetic studies to infer human evolution history and to avoid spurious findings in association testing. Although it is well studied with high-density single nucleotide polymorphisms (SNPs) in genome-wide association studies (GWASs), next-generation sequencing brings both new opportunities and challenges to uncovering population structures in finer scales. Several recent studies have noticed different confounding effects from variants of different minor allele frequencies (MAFs). In this paper, using a low-coverage sequencing dataset from the 1000 Genomes Project, we compared a popular method, principal component analysis (PCA), with a recently proposed spectral clustering technique, called spectral dimensional reduction (SDR), in detectin

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC3864649 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature