Detecting Heterogeneity in Population Structure Across the Genome in Admixed Populations
The genetic structure of human populations is often characterized by aggregating measures of ancestry across the autosomal chromosomes. While it may be reasonable to assume that population structure patterns are similar genome-wide in relatively homogeneous populations, this assumption may not be appropriate for admixed populations, such as Hispanics and African Americans, with recent ancestry from two or more continents. Recent studies have suggested that systematic ancestry differences can arise at genomic locations in admixed populations as a result of selection and non-random mating. Here, we propose a method, which we refer to as the chromosomal ancestry differences (CAnD) test, for detecting heterogeneity in population structure across the genome. CAnD uses local ancestry inferred from SNP genotype data to identify chromosomes harboring genomic regions with ancestry contributions that are significantly different than expected. In simulation studies with real genotype data from Phase III of the HapMap Project, we demonstrate the validity and power of CAnD. We apply CAnD to the HapMap Mexican American (MXL) and African American (ASW) population samples; in this analysis the software RFMix is used to infer local ancestry at genomic regions assuming admixing from Europeans, West Africans, and Native Americans. The CAnD test provides strong evidence of heterogeneity in population structure across the genome in the MXL sample ($p=4e-05$), which is largely driven by elevated Native American ancestry and deficit of European ancestry on the X chromosomes. Among the ASW, all chromosomes are largely African derived and no heterogeneity in population structure is detected in this sample.