期刊
JOURNAL OF ANIMAL SCIENCE
卷 87, 期 6, 页码 1883-1887出版社
OXFORD UNIV PRESS INC
DOI: 10.2527/jas.2008-1259
关键词
animal model; dense marker; marker-assisted selection; reproducing kernel Hilbert spaces; sire model
资金
- Wisconsin Agriculture Experiment Station [DMS-NSF DMS-044371]
Reproducing kernel Hilbert spaces (RKHS) methods are widely used for statistical learning in many areas of endeavor. Recently, these methods have been suggested as a way of incorporating dense markers into genetic models. This note argues that RKHS regression provides a general framework for genetic evaluation that can be used either for pedigree- or marker-based regressions and under any genetic model, infinitesimal or not, and additive or not. Most of the standard models for genetic evaluation, such as infinitesimal animal or sire models, and marker-assisted selection models appear as special cases of RKHS methods.
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