TY - CHAP
T1 - Genomic Best Linear Unbiased Prediction (gBLUP) for the Estimation of Genomic Breeding Values
AU - Clark, Sam A
AU - Van Der Werf, Julius H
PY - 2013
Y1 - 2013
N2 - Genomic best linear unbiased prediction (gBLUP) is a method that utilizes genomic relationships to estimate the genetic merit of an individual. For this purpose, a genomic relationship matrix is used, estimated from DNA marker information. The matrix defines the covariance between individuals based on observed similarity at the genomic level, rather than on expected similarity based on pedigree, so that more accurate predictions of merit can be made. gBLUP has been used for the prediction of merit in livestock breeding, may also have some applications to the prediction of disease risk, and is also useful in the estimation of variance components and genomic heritabilities.
AB - Genomic best linear unbiased prediction (gBLUP) is a method that utilizes genomic relationships to estimate the genetic merit of an individual. For this purpose, a genomic relationship matrix is used, estimated from DNA marker information. The matrix defines the covariance between individuals based on observed similarity at the genomic level, rather than on expected similarity based on pedigree, so that more accurate predictions of merit can be made. gBLUP has been used for the prediction of merit in livestock breeding, may also have some applications to the prediction of disease risk, and is also useful in the estimation of variance components and genomic heritabilities.
KW - Quantitative Genetics (incl Disease and Trait Mapping Genetics)
UR - http://trove.nla.gov.au/version/198468706
U2 - 10.1007/978-1-62703-447-0_13
DO - 10.1007/978-1-62703-447-0_13
M3 - Chapter
SN - 9781627034470
SN - 9781627034463
T3 - Methods in Molecular Biology
SP - 321
EP - 330
BT - Genome-Wide Association Studies and Genomic Prediction
A2 - Gondro, Cedric
A2 - van der Werf, Julius
A2 - Hayes, Ben
PB - Humana Press
CY - New York, United States of America
ER -