J. Comput. Biol. - A spatial haplotype copying model with applications to genotype imputation.

Tópicos

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Resumo

Ever since its introduction, the haplotype copy model has proven to be one of the most successful approaches for modeling genetic variation in human populations, with applications ranging from ancestry inference to genotype phasing and imputation. Motivated by coalescent theory, this approach assumes that any chromosome (haplotype) can be modeled as a mosaic of segments copied from a set of chromosomes sampled from the same population. At the core of the model is the assumption that any chromosome from the sample is equally likely to contribute a priori to the copying process. Motivated by recent works that model genetic variation in a geographic continuum, we propose a new spatial-aware haplotype copy model that jointly models geography and the haplotype copying process. We extend hidden Markov models of haplotype diversity such that at any given location, haplotypes that are closest in the genetic-geographic continuum map are a priori more likely to contribute to the copying process than distant ones. Through simulations starting from the 1000 Genomes data, we show that our model achieves superior accuracy in genotype imputation over the standard spatial-unaware haplotype copy model. In addition, we show the utility of our model in selecting a small personalized reference panel for imputation that leads to both improved accuracy as well as to a lower computational runtime than the standard approach. Finally, we show our proposed model can be used to localize individuals on the genetic-geographical map on the basis of their genotype data.

Resumo Limpo

ever sinc introduct haplotyp copi model proven one success approach model genet variat human popul applic rang ancestri infer genotyp phase imput motiv coalesc theori approach assum chromosom haplotyp can model mosaic segment copi set chromosom sampl popul core model assumpt chromosom sampl equal like contribut priori copi process motiv recent work model genet variat geograph continuum propos new spatialawar haplotyp copi model joint model geographi haplotyp copi process extend hidden markov model haplotyp divers given locat haplotyp closest geneticgeograph continuum map priori like contribut copi process distant one simul start genom data show model achiev superior accuraci genotyp imput standard spatialunawar haplotyp copi model addit show util model select small person refer panel imput lead improv accuraci well lower comput runtim standard approach final show propos model can use local individu geneticgeograph map basi genotyp data

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