Application of Response Surface Methods To Determine Conditions for Optimal Genomic Prediction
An epistatic genetic architecture can have a significant impact on prediction accuracies of genomic prediction (GP) methods. Machine learning methods predict traits comprised of epistatic genetic architectures more accurately than statistical methods based on additive mixed linear models. The differ...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Oxford University Press
2017-09-01
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| Series: | G3: Genes, Genomes, Genetics |
| Subjects: | |
| Online Access: | http://g3journal.org/lookup/doi/10.1534/g3.117.044453 |