Linkage mapping for complex traits : a regression-based approach

Abstract

Linkage analysis makes use of genetic markers to measure genetic similarity between relatives. By comparing this index of genetic similarity with phenotypic similarity, we can identify chromosomal regions harbouring genes involved in the architecture of a phenotype of interest. Although linkage has been very successful in discovering genes responsible for simple Mendelian diseases, results have often been disappointing in gene mapping for complex traits. This thesis presents some attempts to improve the current design and analysis of linkage studies for complex traits. The statistical methodology adopted is driven by the fact that genes involved in complex traits have small effects, it therefore seems legitimate to use score tests because of their local optimality properties. In addition, score tests often give rise to tractable expressions, in the context of linkage these can be meaningfully interpreted in terms of regressions and quickly computed which is a crucial feature in genetics.