Gene mapping by haplotype pattern mining

Abstract

Genetic markers are being increasingly utilized in gene mapping. The discovery of associations between markers and patient phenotypes - such as a disease status - enables the identification of potential disease gene loci. The rationale is that, in diseases with a reasonable genetic contribution, diseased individuals are more likely to have associated marker alleles near the disease susceptibility gene than control individuals. We describe a new gene mapping method-haplotype pattern mining (HPM) - that is based on discovering recurrent marker patterns. We define a class of useful haplotype patterns in genetic case-control data, give an algorithm for finding disease-associated haplotypes, and show how to use them to identify disease susceptibility loci. Experimental studies show that the method has good localization power in data sets with large degrees of phenocopies and with lots of missing and erroneous data. We also demonstrate how the method can be used to discover several genes simultaneously.