Bayesian pedigree inference with small numbers of single nucleotide polymorphisms via a factor-graph representation

Anderson, Eric C.; Ng, Thomas C.

doi:10.1016/j.tpb.2015.09.005

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The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.

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Bayesian pedigree inference with small numbers of single nucleotide polymorphisms via a factor-graph representation

2016
By Anderson, Eric C. ; Ng, Thomas C.
Source: Theoretical Population Biology, 107, 39-51

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Journal Title:

Theoretical Population Biology
Personal Author:

Anderson, Eric C. ; Ng, Thomas C.

Anderson, Eric C. ; Ng, Thomas C. Less -
NOAA Program & Office:

NMFS (National Marine Fisheries Service) ; SWFSC (Southwest Fisheries Science Center)

NMFS (National Marine Fisheries Service) ; SWFSC (Southwest Fisheries Science Center) Less -
Description:

We develop a computational framework for addressing pedigree inference problems using small numbers (80-400) of single nucleotide polymorphisms (SNPs). Our approach relaxes the assumptions, which are commonly made, that sampling is complete with respect to the pedigree and that there is no genotyping error. It relies on representing the inferred pedigree as a factor graph and invoking the Sum-Product algorithm to compute and store quantities that allow the joint probability of the data to be rapidly computed under a large class of rearrangements of the pedigree structure. This allows efficient MCMC sampling over the space of pedigrees, and, hence, Bayesian inference of pedigree structure. In this paper we restrict ourselves to inference of pedigrees without loops using SNPs assumed to be unlinked. We present the methodology in general for multigenerational inference, and we illustrate the method by applying it to the inference of full sibling groups in a large sample (n=1157) of Chinook salmon typed at 95 SNPs. The results show that our method provides a better point estimate and estimate of uncertainty than the currently best-available maximum-likelihood sibling reconstruction method. Extensions of this work to more complex scenarios are briefly discussed.
Keywords:

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Ecology, Evolution, Behavior and Systematics
Source:

Theoretical Population Biology, 107, 39-51
DOI:

https://doi.org/10.1016/j.tpb.2015.09.005
ISSN:

0040-5809
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PDF
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Elsevier BV
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Journal Article
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Accepted Manuscript
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urn:sha-512:51bfc07cef95cda67297e5a6b3fe3fbacc7f0dc53e72432271bb20701535746cc77dcaece410f276131174a9821a58900e441c9e72930c04948662a6e459fd38
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Bayesian pedigree inference with small numbers of single nucleotide polymorphisms via a factor-graph representation

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