Format

Send to

Choose Destination
See comment in PubMed Commons below
Genet Res (Camb). 2008 Dec;90(6):525-40. doi: 10.1017/S0016672308009890.

Inferring genetic values for quantitative traits non-parametrically.

Author information

1
Department of Animal Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA. gianola@ansci.wisc.edu

Abstract

Inferences about genetic values and prediction of phenotypes for a quantitative trait in the presence of complex forms of gene action, issues of importance in animal and plant breeding, and in evolutionary quantitative genetics, are discussed. Current methods for dealing with epistatic variability via variance component models are reviewed. Problems posed by cryptic, non-linear, forms of epistasis are identified and discussed. Alternative statistical procedures are suggested. Non-parametric definitions of additive effects (breeding values), with and without employing molecular information, are proposed, and it is shown how these can be inferred using reproducing kernel Hilbert spaces regression. Two stylized examples are presented to demonstrate the methods numerically. The first example falls in the domain of the infinitesimal model of quantitative genetics, with additive and dominance effects inferred both parametrically and non-parametrically. The second example tackles a non-linear genetic system with two loci, and the predictive ability of several models is evaluated.

PMID:
19123970
DOI:
10.1017/S0016672308009890
[Indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Cambridge University Press
    Loading ...
    Support Center