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Titolo:
Multiple-trait mapping of quantitative trait loci after selective genotyping using logistic regression
Autore:
Henshall, JM; Goddard, ME;
Indirizzi:
Univ New England, Anim Genet & Breeding Unit, Armidale, NSW 2351, Australia Univ New England Armidale NSW Australia 2351 rmidale, NSW 2351, Australia
Titolo Testata:
GENETICS
fascicolo: 2, volume: 151, anno: 1999,
pagine: 885 - 894
SICI:
0016-6731(199902)151:2<885:MMOQTL>2.0.ZU;2-7
Fonte:
ISI
Lingua:
ENG
Soggetto:
FLANKING MARKERS; LINKAGE; CROSSES; DESIGNS; YIELD;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Agriculture,Biology & Environmental Sciences
Life Sciences
Citazioni:
23
Recensione:
Indirizzi per estratti:
Indirizzo: Henshall, JM Univ New England, Anim Genet & Breeding Unit, Armidale, NSW 2351, Australia Univ New England Armidale NSW Australia 2351 2351, Australia
Citazione:
J.M. Henshall e M.E. Goddard, "Multiple-trait mapping of quantitative trait loci after selective genotyping using logistic regression", GENETICS, 151(2), 1999, pp. 885-894

Abstract

Experiments to map QTL usually measure several traits, and not uncommonly genotype only those animals that are extreme for some trait(s). Analysis ofselectively genotyped, multiple-trait data presents special problems, and most simple methods lead to biased estimates of the QTL effects. The use oflogistic regression to estimate QTL effects is described, where the genotype is treated as the dependent variable and the phenotype as the independent variable. In this way selection on phenotype does not bias the results. If normally distributed errors are assumed, the logistic-regression analyis is almost equivalent to a maximum-likelihood analysis, but can be carried out with standard statistical packages, Analysis of a simulated half-sib experiment shows that logistic regression can estimate the effect and positionof a QTL without bias and confirms the increased power achieved by multiple-trait analysis.

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Documento generato il 22/09/20 alle ore 17:14:56