Genomic selection using a fast EM algorythm. 1. Understanding the methodology

R.K. Shepherd; J.A. Woolliams

Genomic selection using a fast EM algorythm. 1. Understanding the methodology

R.K. Shepherd
, J.A. Woolliams

Royal (Dick) School of Veterinary Studies

Research output: Contribution to conference › Abstract

Abstract

The paper uses the technical computer software Mathematica© to explain the features inherent in the procedure emBayesB which is a fast EM algorithm for implementing genomic selection by mapping QTL in genome-wide dense SNP marker data. The prior mixture for a SNP effect and the bimodal shape of the posterior distribution of a SNP effect are displayed graphically, along with visualisations and calculations of how emBayesB estimates genomic breeding values. The companion paper (Shepherd et al. 2009) uses emBayesB to analyse simulated data.

Original language	Undefined/Unknown
Pages	83
Number of pages	1
Publication status	Published - 2009
Event	Association for the Advancement of Animal Breeding and Genetics - Barossa Valley, Australia Duration: 28 Sept 2009 → 1 Oct 2009

Conference

Conference	Association for the Advancement of Animal Breeding and Genetics
Country/Territory	Australia
City	Barossa Valley
Period	28/09/09 → 1/10/09

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Cite this

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title = "Genomic selection using a fast EM algorythm. 1. Understanding the methodology",

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N2 - The paper uses the technical computer software Mathematica© to explain the features inherent in the procedure emBayesB which is a fast EM algorithm for implementing genomic selection by mapping QTL in genome-wide dense SNP marker data. The prior mixture for a SNP effect and the bimodal shape of the posterior distribution of a SNP effect are displayed graphically, along with visualisations and calculations of how emBayesB estimates genomic breeding values. The companion paper (Shepherd et al. 2009) uses emBayesB to analyse simulated data.

AB - The paper uses the technical computer software Mathematica© to explain the features inherent in the procedure emBayesB which is a fast EM algorithm for implementing genomic selection by mapping QTL in genome-wide dense SNP marker data. The prior mixture for a SNP effect and the bimodal shape of the posterior distribution of a SNP effect are displayed graphically, along with visualisations and calculations of how emBayesB estimates genomic breeding values. The companion paper (Shepherd et al. 2009) uses emBayesB to analyse simulated data.

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T2 - Association for the Advancement of Animal Breeding and Genetics

Y2 - 28 September 2009 through 1 October 2009

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