Parsimonious and powerful composite likelihood testing for group difference and genotype-phenotype association

Abstract

Studying the association between a phenotype and a number of genetic variants from case-control data is an important goal in many genetic studies. Association analysis is often carried out by testing the null hypothesis that two groups of multi-dimensional data are generated by the same population. Testing based on genotype data is a challenging task as the full likelihood of the data is usually intractable. This difficulty may be tackled by composite likelihood (MCL) tests which do not entail the full likelihood. But currently available MCL tests are subject to severe power loss for involving non-informative or redundant sub-likelihoods. To reduce the power loss, a forward search and test m..