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On the use of linear regression and maximum likelihood for QTL mapping in half-sib designs

Published online by Cambridge University Press:  01 October 1998

P. V. BARET ,
S. A. KNOTT  and
P. M. VISSCHER
P. V. BARET
Affiliation:
University of Edinburgh, Institute of Cell, Animal and Population Biology, West Mains Road, Edinburgh EH9 3JT, Scotland Present address: Université catholique de Louvain, Faculté des sciences agronomiques, Unité de Génétique, Place Croix du Sud 2 bte 14, B-1348 Louvain-la-Neuve, Belgium. Telephone: +32 10 47.37.23. Fax: +32 10 47.37.28. e-mail: [email protected].
S. A. KNOTT
Affiliation:
University of Edinburgh, Institute of Cell, Animal and Population Biology, West Mains Road, Edinburgh EH9 3JT, Scotland
P. M. VISSCHER
Affiliation:
University of Edinburgh, Institute of Ecology and Resources Management, West Mains Road, Edinburgh EH9 3JG, Scotland
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Abstract

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Methods of identification of quantitative trait loci (QTL) using a half-sib design are generally based on least-squares or maximum likelihood approaches. These methods differ in the genetical model considered and in the information used. Despite these differences, the power of the two methods in a daughter design is very similar. Using an analogy with a one-way analysis of variance, we propose an equation connecting the two test-statistics (F ratio for regression and likelihood ratio test in the case of the maximum likelihood). The robustness of this relationship is tested by simulation for different single QTL models. In general, the correspondence between the two statistics is good under both the null hypothesis and the alternative hypothesis of a single QTL segregating. Practical implications are discussed with particular emphasis on the theoretical distribution of the likelihood ratio test.

Type
Research Article
Information
Genetics Research , Volume 72 , Issue 2 , October 1998 , pp. 149 - 158
Copyright
© 1998 Cambridge University Press