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A generic hidden Markov model for multiparent populations

A common step in the analysis of multiparent populations (MPPs) is genotype reconstruction: identifying the founder origin of haplotypes from dense marker data. This process often makes use of a probability model for the pattern of founder alleles along chromosomes, including the relative frequency...

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Detalles Bibliográficos
Autor principal: Broman, Karl W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9210298/
https://www.ncbi.nlm.nih.gov/pubmed/34791211
http://dx.doi.org/10.1093/g3journal/jkab396
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author Broman, Karl W
author_facet Broman, Karl W
author_sort Broman, Karl W
collection PubMed
description A common step in the analysis of multiparent populations (MPPs) is genotype reconstruction: identifying the founder origin of haplotypes from dense marker data. This process often makes use of a probability model for the pattern of founder alleles along chromosomes, including the relative frequency of founder alleles and the probability of exchanges among them, which depend on a model for meiotic recombination and on the mating design for the population. While the precise experimental design used to generate the population may be used to derive a precise characterization of the model for exchanges among founder alleles, this can be tedious, particularly given the great variety of experimental designs that have been proposed. We describe an approximate model that can be applied for a variety of MPPs. We have implemented the approach in the R/qtl2 software, and we illustrate its use in applications to publicly available data on Diversity Outbred and Collaborative Cross mice.
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spelling pubmed-92102982022-06-21 A generic hidden Markov model for multiparent populations Broman, Karl W G3 (Bethesda) Investigation A common step in the analysis of multiparent populations (MPPs) is genotype reconstruction: identifying the founder origin of haplotypes from dense marker data. This process often makes use of a probability model for the pattern of founder alleles along chromosomes, including the relative frequency of founder alleles and the probability of exchanges among them, which depend on a model for meiotic recombination and on the mating design for the population. While the precise experimental design used to generate the population may be used to derive a precise characterization of the model for exchanges among founder alleles, this can be tedious, particularly given the great variety of experimental designs that have been proposed. We describe an approximate model that can be applied for a variety of MPPs. We have implemented the approach in the R/qtl2 software, and we illustrate its use in applications to publicly available data on Diversity Outbred and Collaborative Cross mice. Oxford University Press 2021-11-16 /pmc/articles/PMC9210298/ /pubmed/34791211 http://dx.doi.org/10.1093/g3journal/jkab396 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Investigation
Broman, Karl W
A generic hidden Markov model for multiparent populations
title A generic hidden Markov model for multiparent populations
title_full A generic hidden Markov model for multiparent populations
title_fullStr A generic hidden Markov model for multiparent populations
title_full_unstemmed A generic hidden Markov model for multiparent populations
title_short A generic hidden Markov model for multiparent populations
title_sort generic hidden markov model for multiparent populations
topic Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9210298/
https://www.ncbi.nlm.nih.gov/pubmed/34791211
http://dx.doi.org/10.1093/g3journal/jkab396
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