Gene Mapping by Pattern Discovery

The objective of gene mapping is to localize genes responsible for a particular disease or trait. We consider association-based gene mapping, where the data consist of markers genotyped for a sample of independent case and control individuals. In this chapter we give a generic framework for nonparametric gene mapping based on pattern discovery. We have previously introduced two instances of the framework: haplotype pattern mining (HPM) for case—control haplotype material and QHPM for quantitative trait and covariates. In our experiments, HPM has proven to be very competitive compared to other methods. Geneticists have found the output of HPM useful, and today HPM is routinely used for analyses by several research groups. We review these methods and present a novel instance, HPM-G, suitable for directly analyzing phase-unknown genotype data. Obtaining haplotypes is more costly than obtaining phase-unknown genotypes, and our experiments show that although larger samples are needed with HPMG, it is still in many cases more cost-effective than analysis with haplotype data.