| Title |
|
Genomic Best Linear Unbiased Prediction (gBLUP) for the Estimation of Genomic Breeding Values |
|
|
| Publication Date |
|
| Author(s) |
|
| Editor |
|
Editor(s): Cedric Gondro, Julius van der Werf, Ben Hayes |
|
|
| Type of document |
|
| Language |
|
| Entity Type |
|
| Publisher |
|
| Place of publication |
|
New York, United States of America |
|
|
| Edition |
|
| Series |
|
Methods in Molecular Biology |
|
|
| DOI |
|
10.1007/978-1-62703-447-0_13 |
|
|
| UNE publication id |
|
| Abstract |
|
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. |
|
|
| Link |
|
| Citation |
|
Genome-Wide Association Studies and Genomic Prediction, p. 321-330 |
|
|
| ISBN |
|
| Start page |
|
| End page |
|