Score test for mapping quantitative-trait loci with sibships of arbitrary size when the dominance effect is not negligible

Kai Wang, Jian Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

9 Citations (Scopus)

Abstract

In the linakge analysis of quantitative traits, an additive model that assumes no dominance effect is often adopted. Intuitively, when the no-dominance-effect assumption does not hold, such a practice does not make efficient use of the data, and its power to detect linkage can be improved. Here we introduce a score statistic for detecting quantitative trait loci when the dominance effect is not neglible or the dominance effect is a concern. This statistic is derived from a normal likelihood function for sibships of arbitrary size. In the derivation, the inherent genetic constraints on model parameters are fully taken into consideration. This score statistic is asymptotically equivalent to the corresponding likelihood ratio statistic, but it is much easier to compute. The asymptotic distribution of this statistic is derived, which is a mixture of X02, X12, and X22. Weights for distribution components are functions of the informativeness of the marker data. The type I error rate and the power of the proposed statistic in finite sample are evaluated via simulations.
Original languageEnglish
Pages (from-to)398-412
Number of pages15
JournalGenetic Epidemiology
Volume23
Issue number4
DOIs
Publication statusPublished - 1 Nov 2002
Externally publishedYes

Keywords

  • Additive effect
  • Dominance effect
  • Likelihood ratio statistic
  • Linkage analysis
  • QTL
  • Score statistic

ASJC Scopus subject areas

  • Epidemiology
  • Genetics(clinical)

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