Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

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Record number 393612
Title Identity-by-Descent Matrix Decomposition Using Latent Ancestral Allele Models
Author(s) Braak, C.J.F. ter; Boer, M.P.; Totir, L.; Winkler, C.R.; Smith, O.S.; Bink, M.C.A.M.
Source Genetics 185 (2010)3. - ISSN 0016-6731 - p. 1045 - 1057.
Department(s) Biometris
Mathematical and Statistical Methods - Biometris
Publication type Refereed Article in a scientific journal
Publication year 2010
Keyword(s) quantitative trait loci - population-structure - plant-populations - genotype data - association - stratification - prediction - regression - selection - markers
Abstract Genetic linkage and association studies are empowered by proper modeling of relatedness among individuals. Such relatedness can be inferred from marker and/or pedigree information. In this study, the genetic relatedness among n inbred individuals at a particular locus is expressed as an n x n square matrix Q. The elements of Q are identity-by-descent probabilities, that is, probabilities that two individuals share an allele descended from a common ancestor. In this representation the definition of the ancestral alleles and their number remains implicit. For human inspection and further analysis, an explicit representation in terms of the ancestral allele origin and the number of alleles is desirable. To this purpose, we decompose the matrix Q by a latent class model with K classes (latent ancestral alleles). Let P be an n x K matrix with assignment probabilities of n individuals to K classes constrained such that every element is nonnegative and each row sums to 1. The problem then amounts to approximating Q by PPT, while disregarding the diagonal elements. This is not an eigenvalue problem because of the constraints on P. An efficient algorithm for calculating P is provided. We indicate the potential utility of the latent ancestral allele model. For representative locus-specific Q matrices constructed for a set of maize inbreds, the proposed model recovered the known ancestry.
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