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Fast individual ancestry inference from DNA sequence data leveraging allele frequencies for multiple populations

BACKGROUND: Estimation of individual ancestry from genetic data is useful for the analysis of disease association studies, understanding human population history and interpreting personal genomic variation. New, computationally efficient methods are needed for ancestry inference that can effectively...

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Autores principales: Bansal, Vikas, Libiger, Ondrej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4301802/
https://www.ncbi.nlm.nih.gov/pubmed/25592880
http://dx.doi.org/10.1186/s12859-014-0418-7
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author Bansal, Vikas
Libiger, Ondrej
author_facet Bansal, Vikas
Libiger, Ondrej
author_sort Bansal, Vikas
collection PubMed
description BACKGROUND: Estimation of individual ancestry from genetic data is useful for the analysis of disease association studies, understanding human population history and interpreting personal genomic variation. New, computationally efficient methods are needed for ancestry inference that can effectively utilize existing information about allele frequencies associated with different human populations and can work directly with DNA sequence reads. RESULTS: We describe a fast method for estimating the relative contribution of known reference populations to an individual’s genetic ancestry. Our method utilizes allele frequencies from the reference populations and individual genotype or sequence data to obtain a maximum likelihood estimate of the global admixture proportions using the BFGS optimization algorithm. It accounts for the uncertainty in genotypes present in sequence data by using genotype likelihoods and does not require individual genotype data from external reference panels. Simulation studies and application of the method to real datasets demonstrate that our method is significantly times faster than previous methods and has comparable accuracy. Using data from the 1000 Genomes project, we show that estimates of the genome-wide average ancestry for admixed individuals are consistent between exome sequence data and whole-genome low-coverage sequence data. Finally, we demonstrate that our method can be used to estimate admixture proportions using pooled sequence data making it a valuable tool for controlling for population stratification in sequencing based association studies that utilize DNA pooling. CONCLUSIONS: Our method is an efficient and versatile tool for estimating ancestry from DNA sequence data and is available from https://sites.google.com/site/vibansal/software/iAdmix. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-014-0418-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-43018022015-02-03 Fast individual ancestry inference from DNA sequence data leveraging allele frequencies for multiple populations Bansal, Vikas Libiger, Ondrej BMC Bioinformatics Methodology Article BACKGROUND: Estimation of individual ancestry from genetic data is useful for the analysis of disease association studies, understanding human population history and interpreting personal genomic variation. New, computationally efficient methods are needed for ancestry inference that can effectively utilize existing information about allele frequencies associated with different human populations and can work directly with DNA sequence reads. RESULTS: We describe a fast method for estimating the relative contribution of known reference populations to an individual’s genetic ancestry. Our method utilizes allele frequencies from the reference populations and individual genotype or sequence data to obtain a maximum likelihood estimate of the global admixture proportions using the BFGS optimization algorithm. It accounts for the uncertainty in genotypes present in sequence data by using genotype likelihoods and does not require individual genotype data from external reference panels. Simulation studies and application of the method to real datasets demonstrate that our method is significantly times faster than previous methods and has comparable accuracy. Using data from the 1000 Genomes project, we show that estimates of the genome-wide average ancestry for admixed individuals are consistent between exome sequence data and whole-genome low-coverage sequence data. Finally, we demonstrate that our method can be used to estimate admixture proportions using pooled sequence data making it a valuable tool for controlling for population stratification in sequencing based association studies that utilize DNA pooling. CONCLUSIONS: Our method is an efficient and versatile tool for estimating ancestry from DNA sequence data and is available from https://sites.google.com/site/vibansal/software/iAdmix. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-014-0418-7) contains supplementary material, which is available to authorized users. BioMed Central 2015-01-16 /pmc/articles/PMC4301802/ /pubmed/25592880 http://dx.doi.org/10.1186/s12859-014-0418-7 Text en © Bansal and Libiger; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology Article
Bansal, Vikas
Libiger, Ondrej
Fast individual ancestry inference from DNA sequence data leveraging allele frequencies for multiple populations
title Fast individual ancestry inference from DNA sequence data leveraging allele frequencies for multiple populations
title_full Fast individual ancestry inference from DNA sequence data leveraging allele frequencies for multiple populations
title_fullStr Fast individual ancestry inference from DNA sequence data leveraging allele frequencies for multiple populations
title_full_unstemmed Fast individual ancestry inference from DNA sequence data leveraging allele frequencies for multiple populations
title_short Fast individual ancestry inference from DNA sequence data leveraging allele frequencies for multiple populations
title_sort fast individual ancestry inference from dna sequence data leveraging allele frequencies for multiple populations
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4301802/
https://www.ncbi.nlm.nih.gov/pubmed/25592880
http://dx.doi.org/10.1186/s12859-014-0418-7
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