title: Accurate inference of local phased ancestry of modern admixed populations.
abstract: Population stratification is a growing concern in genetic-association studies. Averaged ancestry at the genome level (global ancestry) is insufficient for detecting the population substructures and correcting population stratifications in association studies. Local and phase stratification are needed for human genetic studies, but current technologies cannot be applied on the entire genome data due to various technical caveats. Here we developed a novel approach (aMAP, ancestry of Modern Admixed Populations) for inferring local phased ancestry. It took about 3 seconds on a desktop computer to finish a local ancestry analysis for each human genome with 1.4-million SNPs. This method also exhibits the scalability to larger datasets with respect to the number of SNPs, the number of samples, and the size of reference panels. It can detect the lack of the proxy of reference panels. The accuracy was 99.4%. The aMAP software has a capacity for analyzing 6-way admixed individuals. As the biomedical community continues to expand its efforts to increase the representation of diverse populations, and as the number of large whole-genome sequence datasets continues to grow rapidly, there is an increasing demand on rapid and accurate local ancestry analysis in genetics, pharmacogenomics, population genetics, and clinical diagnosis.
authors: 1] Cardiovascular Research Institute, Morehouse School of Medicine, Atlanta, Georgia, USA [2].
authors: Yamin
authors: Y
authors: Ma
authors: 1] DNAncestree Inc, Atlanta, Georgia, USA [2].
authors: Jian
authors: J
authors: Zhao
authors: Cardiovascular Research Institute, Morehouse School of Medicine, Atlanta, Georgia, USA.
authors: Jian-Syuan
authors: JS
authors: Wong
authors: Cardiovascular Research Institute, Morehouse School of Medicine, Atlanta, Georgia, USA.
authors: Li
authors: L
authors: Ma
authors: Cardiovascular Research Institute, Morehouse School of Medicine, Atlanta, Georgia, USA.
authors: Wenzhi
authors: W
authors: Li
authors: Cardiovascular Research Institute, Morehouse School of Medicine, Atlanta, Georgia, USA.
authors: Guoxing
authors: G
authors: Fu
authors: Cardiovascular Research Institute, Morehouse School of Medicine, Atlanta, Georgia, USA.
authors: Wei
authors: W
authors: Xu
authors: Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA.
authors: Kui
authors: K
authors: Zhang
authors: Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA.
authors: Rick A
authors: RA
authors: Kittles
authors: Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
authors: Yun
authors: Y
authors: Li
authors: Cardiovascular Research Institute, Morehouse School of Medicine, Atlanta, Georgia, USA.
authors: Qing
authors: Q
authors: Song
mesh_terms: D000465:Algorithms; D002874:Chromosome Mapping; D003198:Computer Simulation; D005789:Genealogy and Heraldry; D056726:Genetic Association Studies; D005828:Genetics, Population; D015894:Genome, Human; D055106:Genome-Wide Association Study; D006801:Humans; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software