QTL Mapping Under Ascertainment

J. Peng 1 and D. Siegmund2

1Department of Statistics, University of California, Davis, CA 95616

2Department of Statistics, Stanford University, Stanford, CA 94305 California 94305, USA

Correspondence author: jie@wald.ucdavis.edu

Abstract:

Mapping quantitative trait loci (QTL) using ascertained sibships is discussed. It is shown that under the standard normality assumption of variance components analysis the efficient scores are unchanged by ascertainment, and two different schemes of ascertainment correction suggested in the literature are asymptotically equivalent. The use of conditional maximum likelihood estimators derived under the normality assumption to estimate nuisance parameters is shown to result in only a small loss of power compared to the case of known parameters, even when the distribution of phenotypes is non-normal and/or the ascertainment criterion is ill defined.

Keywords: Gene mapping, Quantitative trait, Ascertainment, Efficient score.