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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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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. |
format | Online Article Text |
id | pubmed-4301802 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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