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Modeling population structure under hierarchical Dirichlet processes

Iorio, MD; Elliott, LT; Favaro, S; Adhikari, K; Teh, YW; (2019) Modeling population structure under hierarchical Dirichlet processes. Bayesian Analysis , 14 (2) pp. 313-339. 10.1214/17-BA1093. Green open access

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Abstract

We propose a Bayesian nonparametric model to infer population admixture, extending the Hierarchical Dirichlet Process to allow for correlation between loci due to Linkage Disequilibrium. Given multilocus genotype data from a sample of individuals, the model allows inferring classifying individuals as unadmixed or admixed, inferring the number of subpopulations ancestral to an admixed population and the population of origin of chromosomal regions. Our model does not assume any specific mutation process and can be applied to most of the commonly used genetic markers. We present a MCMC algorithm to perform posterior inference from the model and discuss methods to summarise the MCMC output for the analysis of population admixture. We demonstrate the performance of the proposed model in simulations and in a real application, using genetic data from the EDAR gene, which is considered to be ancestry-informative due to well-known variations in allele frequency as well as phenotypic effects across ancestry. The structure analysis of this dataset leads to the identification of a rare haplotype in Europeans.

Type: Article
Title: Modeling population structure under hierarchical Dirichlet processes
Open access status: An open access version is available from UCL Discovery
DOI: 10.1214/17-BA1093
Publisher version: http://doi.org/10.1214/17-BA1093
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: stat.AP, stat.AP, stat.ME, stat.OT
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Cell and Developmental Biology
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/1467084
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