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Use of principal component and factor analysis to reduce the number of independent variables in the prediction of genomic breeding values

Macciotta, Nicolò Pietro Paolo and Gaspa, Giustino (2009) Use of principal component and factor analysis to reduce the number of independent variables in the prediction of genomic breeding values. Italian Journal of Animal Science, Vol. 8 (Suppl. 2), p. 105-107. ISSN 1828-051X. Article.

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Abstract

On a simulated population of 2,500 individuals, Principal Component Analysis and Factor Analysis were used to reduce the number of independent variables for the prediction of GEBVs. A genome of 100 cM with 300 bialleic SNPs and 20 multiallelic QTLs was considered. Two heritabilities (0.2 and 0.5) were tested. Multivariate reduction methods performed better than the traditional BLUP with all the SNPs, either on generations with phenotypes available or on those without phenotypes, especially in the low heritability scenario (about 0.70 vs. 0.45 in generations without phenotypes). The use of multivariate reduction techniques on the considered data set resulted in a simplification of calculations (reduction of about 90% of predictors) and in an improvement of GEBV accuracies.

Item Type:Article
ID Code:3014
Status:Published
Refereed:Yes
Uncontrolled Keywords:Principal component analysis, factor analysis, genome wide selection
Subjects:Area 07 - Scienze agrarie e veterinarie > AGR/17 Zootecnica generale e miglioramento genetico
Divisions:001 Università di Sassari > 01 Dipartimenti > Scienze zootecniche
Publisher:Avenue media on behalf of Scientific Association of Animal Production (ASPA)
ISSN:1828-051X
Publisher Policy:Depositato per gentile concessione dell'ASPA
Additional Information:Relazione presentata al 18. Congresso nazionale ASPA, Palermo, 9-12 giugno 2009.
Deposited On:18 Sep 2009 10:33

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