Literature DB >> 24210252

Accurate local-ancestry inference in exome-sequenced admixed individuals via off-target sequence reads.

Youna Hu1, Cristen Willer, Xiaowei Zhan, Hyun Min Kang, Gonçalo R Abecasis.   

Abstract

Estimates of the ancestry of specific chromosomal regions in admixed individuals are useful for studies of human evolutionary history and for genetic association studies. Previously, this ancestry inference relied on high-quality genotypes from genome-wide association study (GWAS) arrays. These high-quality genotypes are not always available when samples are exome sequenced, and exome sequencing is the strategy of choice for many ongoing genetic studies. Here we show that off-target reads generated during exome-sequencing experiments can be combined with on-target reads to accurately estimate the ancestry of each chromosomal segment in an admixed individual. To reconstruct local ancestry, our method SEQMIX models aligned bases directly instead of relying on hard genotype calls. We evaluate the accuracy of our method through simulations and analysis of samples sequenced by the 1000 Genomes Project and the NHLBI Grand Opportunity Exome Sequencing Project. In African Americans, we show that local-ancestry estimates derived by our method are very similar to those derived with Illumina's Omni 2.5M genotyping array and much improved in relation to estimates that use only exome genotypes and ignore off-target sequencing reads. Software implementing this method, SEQMIX, can be applied to analysis of human population history or used for genetic association studies in admixed individuals.
Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 24210252      PMCID: PMC3824118          DOI: 10.1016/j.ajhg.2013.10.008

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


  34 in total

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  12 in total

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

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10.  Analysis of Racial/Ethnic Representation in Select Basic and Applied Cancer Research Studies.

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