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Estimation of Genetic Effects and Genotype-Phenotype Maps

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Publication Date: 28 Jun 2008

Journal: Evolutionary Bioinformatics 2008:4 225-235

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Abstract Arnaud Le Rouzic1 and José M. Álvarez-Castro2

1Center for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway. 2Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.

Abstract

Determining the genetic architecture of complex traits is a necessary step to understand phenotypic changes in natural, experimental and domestic populations. However, this is still a major challenge for modern genetics, since the estimation of genetic effects tends to be complicated by genetic interactions, which lead to changes in the effect of allelic substitutions depending on the genetic background. Recent progress in statistical tools aiming to describe and quantify genetic effects meaningfully improves the efficiency and the availability of genotype-to-phenotype mapping methods. In this contribution, we facilitate the practical use of the recently published ‘NOIA’ quantitative framework by providing an implementation of linear and multilinear regressions, change of reference operation and genotype-to-phenotype mapping in a package (‘noia’) for the software R, and we discuss theoretical and practical benefits evolutionary and quantitative geneticists may find in using proper modeling strategies to quantify the effects of genes.


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Posted by Arnaud Le Rouzic - 16:01,December 07, 2009

** Corrigendum ** "Estimation of Genetic Effects and Genotype-Phenotype Maps", Evolutionary Bioinformatics 2008:4 225-235, Arnaud Le Rouzic and José M. Álvarez-Castro Equation (6) page 227 should be read as: V = 1 . Diag(F) (S o S) (Diag(E) o Diag(E)) Where '1' is a vector of ones, Diag(F) stands for a diagonal matrix with the vector F as the diagonal and 0 elsewhere, and 'o' represents the Hadamard (pairwise) product. The published version of the equation had non-conformable arguments and could not lead to any result. With our apologizes, Arnaud Le Rouzic and José Álvarez-Castro.


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