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Accurate Inference of Local Phased Ancestry of Modern Admixed Populations

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 neede...

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Autores principales: Ma, Yamin, Zhao, Jian, Wong, Jian-Syuan, Ma, Li, Li, Wenzhi, Fu, Guoxing, Xu, Wei, Zhang, Kui, Kittles, Rick A., Li, Yun, Song, Qing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4107375/
https://www.ncbi.nlm.nih.gov/pubmed/25052506
http://dx.doi.org/10.1038/srep05800
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author Ma, Yamin
Zhao, Jian
Wong, Jian-Syuan
Ma, Li
Li, Wenzhi
Fu, Guoxing
Xu, Wei
Zhang, Kui
Kittles, Rick A.
Li, Yun
Song, Qing
author_facet Ma, Yamin
Zhao, Jian
Wong, Jian-Syuan
Ma, Li
Li, Wenzhi
Fu, Guoxing
Xu, Wei
Zhang, Kui
Kittles, Rick A.
Li, Yun
Song, Qing
author_sort Ma, Yamin
collection PubMed
description 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.
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spelling pubmed-41073752014-08-20 Accurate Inference of Local Phased Ancestry of Modern Admixed Populations Ma, Yamin Zhao, Jian Wong, Jian-Syuan Ma, Li Li, Wenzhi Fu, Guoxing Xu, Wei Zhang, Kui Kittles, Rick A. Li, Yun Song, Qing Sci Rep Article 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. Nature Publishing Group 2014-07-23 /pmc/articles/PMC4107375/ /pubmed/25052506 http://dx.doi.org/10.1038/srep05800 Text en Copyright © 2014, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/
spellingShingle Article
Ma, Yamin
Zhao, Jian
Wong, Jian-Syuan
Ma, Li
Li, Wenzhi
Fu, Guoxing
Xu, Wei
Zhang, Kui
Kittles, Rick A.
Li, Yun
Song, Qing
Accurate Inference of Local Phased Ancestry of Modern Admixed Populations
title Accurate Inference of Local Phased Ancestry of Modern Admixed Populations
title_full Accurate Inference of Local Phased Ancestry of Modern Admixed Populations
title_fullStr Accurate Inference of Local Phased Ancestry of Modern Admixed Populations
title_full_unstemmed Accurate Inference of Local Phased Ancestry of Modern Admixed Populations
title_short Accurate Inference of Local Phased Ancestry of Modern Admixed Populations
title_sort accurate inference of local phased ancestry of modern admixed populations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4107375/
https://www.ncbi.nlm.nih.gov/pubmed/25052506
http://dx.doi.org/10.1038/srep05800
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