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Local and global ancestry inference and applications to genetic association analysis for admixed populations.

ABSTRACT: Genetic association studies in recently admixed populations offer exciting opportunities to identify novel variants underlying phenotypic diversity. At the same time, genetic heterogeneity resulting from population admixture has to be accounted for to ensure validity of association tests. The whole-genome sequence data and the genome-wide single-nucleotide polymorphism chip data for Mexican American individuals provided by Genetic Analysis Workshop 18 (GAW18) presents a unique opportunity to evaluate and compare methods for the statistical analysis of admixed genetic data. We summarize here the five contributions from the GAW18 working group on admixture mapping and adjusting for admixture. Although group members considered a variety of research topics, the general theme was inference and consideration of ancestry admixture in genetic analyses. The topics considered can be grouped into three categories: (1) global and local ancestry inference and estimation, (2) association and admixture mapping, and (3) genotype imputation in admixed samples. We describe the approaches that were used and the most relevant findings from each contribution. We also provide insight into the strengths and limitations of the state-of-the-art methods considered for genetic analyses in admixed populations.

SUBMITTER: Thornton TA

PROVIDER: S-EPMC4339867 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Local and global ancestry inference and applications to genetic association analysis for admixed populations.

Thornton Timothy A TA Bermejo Justo Lorenzo JL

Genetic epidemiology 20140901

Genetic association studies in recently admixed populations offer exciting opportunities to identify novel variants underlying phenotypic diversity. At the same time, genetic heterogeneity resulting from population admixture has to be accounted for to ensure validity of association tests. The whole-genome sequence data and the genome-wide single-nucleotide polymorphism chip data for Mexican American individuals provided by Genetic Analysis Workshop 18 (GAW18) presents a unique opportunity to eva ...[more]

PMID: 25112189

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Project description:Human populations have interacted throughout history, and a considerable portion of modern human populations show evidence of admixture. Local ancestry inference (LAI) is focused on detecting the genetic ancestry of chromosomal segments in admixed individuals and has wide applications. In this work, we proposed a new LAI method based on population-specific single-nucleotide polymorphisms (SNPs) and applied it in the analysis of admixed populations in the 1000 Genomes Project (1KGP). Based on population-specific SNPs in a sliding window, we computed local ancestry information vectors, which are moment estimators of local ancestral proportions, for two haplotypes of an admixed individual and inferred the local ancestral origins. Then we used African (AFR), East Asian (EAS), European (EUR) and South Asian (SAS) populations from the 1KGP and indigenous American (AMR) populations from the Human Genome Diversity Project (HGDP) as reference populations and conducted the proposed LAI analysis on African American populations and American populations in the 1KGP. The results were compared with those obtained by RFMix, G-Nomix and FLARE. We demonstrated that the existence of alleles in a chromosomal region that are specific to a particular reference population and the absence of alleles specific to the other reference populations provide reasonable evidence for determining the ancestral origin of the region. Contemporary AFR, AMR and EUR populations approximate ancestral populations of the admixed populations well, and the results from RFMix, G-Nomix and FLARE largely agree with those from the Ancestral Spectrum Analyzer (ASA), in which the proposed method was implemented. When admixtures are ancient and contemporary reference populations do not satisfactorily approximate ancestral populations, the performances of RFMix, G-Nomix and FLARE deteriorate with increased error rates and fragmented chromosomal segments. In contrast, our method provides fair results.

Dataset Information

Local and global ancestry inference and applications to genetic association analysis for admixed populations.

Publications

Local and global ancestry inference and applications to genetic association analysis for admixed populations.

Similar Datasets

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