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Disentangling Pleiotropy along the Genome using Sparse Latent Variable Models

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Bayesian models are described that use atent variables to model covariances. These models are flexible, scale up linearly in the number of traits, and allow
separating covariance structures in different components at the trait level and at the genomic level. Multi-trait version of the BayesA (MT-BA) and Bayesian LASSO (MT-BL) are described that model heterogeneous variance and covariance over the genome, and a model that directly models multiple genomic breeding values (MT-MG), representing different genomic covariance structures. The models are demonstrated on a mouse data set to model the genomic covariances between body weight, feed intake and feed efficiency.
Original languageEnglish
Publication year17 Aug 2014
Number of pages4
Publication statusPublished - 17 Aug 2014
Event10th World Congress on Genetics Applied to Livestock Production (WCGALP) - The Westin Bayshore, 1601 Bayshore Drive, Vancouver, BC V6G 2V4, Vancouver, Canada
Duration: 17 Aug 201422 Aug 2014
Conference number: 10th

Conference

Conference10th World Congress on Genetics Applied to Livestock Production (WCGALP)
Number10th
LocationThe Westin Bayshore, 1601 Bayshore Drive, Vancouver, BC V6G 2V4
CountryCanada
CityVancouver
Period17/08/201422/08/2014

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