Local and Global Stratification Analysis in Whole Genome Sequencing (WGS) Studies Using LocStra

Abstract

We are interested in the analysis of local and global population stratification in WGS studies. We present a new R package (locStra) that utilizes the covariance matrix, the genomic relationship matrix, and the unweighted/weighted genetic Jaccard similarity matrix in order to assess population substructure. The package allows one to use a tailored sliding window approach, for instance using user-defined window sizes and metrics, in order to compare local and global similarity matrices. A technique to select the window size is proposed. Population stratification with locStra is efficient due to its C++ implementation which fully exploits sparse matrix algebra. The runtime for the genome-wide computation of all local similarity matrices does typically not exceed one hour for realistic study sizes. This makes an unprecedented investigation of local stratification across the entire genome possible. We apply our package to the 1,000 Genomes Project.