QTL mapping using logistic regression

Title
QTL mapping using logistic regression
Publication Date
2005
Author(s)
Zhang, Yuandan
( author )
OrcID: https://orcid.org/0000-0002-1998-3313
Email: yzhang4@une.edu.au
UNE Id une-id:yzhang4
Tier, Bruce
Editor
Editor(s): AAABG: Association for the Advancement of Animal Breeding and Genetics
Type of document
Conference Publication
Language
en
Entity Type
Publication
Place of publication
Collingwood, Australia
UNE publication id
une:4609
Abstract
This study compares logistic regression (LR) with maximum likelihood (ML) for mapping quantitative trait loci (QTL) in halfsib family with respect to genotyping schemes (full and selective), various levels of marker informativeness and marker interval. Under selective genotyping, the power of ML is limited in regions with low information contents. In this case, LR performed better than ML and provides a straightforward and robust solution to such situation.
Link
link
Citation
Proceedings of the Association for the Advancement of Animal Breeding and Genetics, v.16, p. 354-357
ISSN
1328-3227
ISBN
064309234X
0643092331
Start page
354
End page
357

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