An efficient strategy to characterize alleles and complex haplotypes using DNA-markers

TL;DR

This paper introduces an efficient statistical method to identify and estimate associations between traits and haplotypes using DNA-markers, even without direct access to the haplotypes, by grouping marker-alleles and employing penalized likelihood techniques.

Contribution

It proposes a novel approach combining combinatorial search and penalized likelihood to detect and infer haplotypes associated with traits from marker data.

Findings

Method effectively identifies associated haplotypes

Supports inference of the number of detectable haplotypes

Applicable with standard statistical tools for moderate marker sets

Abstract

We consider the problem of detecting and estimating the strength of association between a trait of interest and alleles or haplotypes in a small genomic region (e.g. a gene or a gene complex), when no direct information on that region is available but the values of neighbouring DNA-markers are at hand. We argue that the effects of the non-observable haplotypes of the genomic regions can and should be represented by factors representing disjoint groups of marker-alleles. A theoretical argument based on a hypothetical phylogenetic tree supports this general claim. The techniques described allow to identify and to infer the number of detectable haplotypes in the genomic region that are associated with a trait. The methods proposed use an exhaustive combinatorial search coupled with the maximization of a version of the likelihood function penalized for the number of parameters. This procedure can easily be implemented with standard statistical methods for a moderate number of marker-alleles.