The recent data release of the Haplotype Mapping (HapMap) project, and
the rapid reduction in genotyping costs, open new directions and
opportunities in the study of complex diseases via the analysis of
single nucleotide polymorphisms (SNPs) data. At the same time, the
increased size of the SNP datasets set new computational and statistical
challenges.
In this talk I will discuss some of the computational challenges set by
these large-scale studies, and the current solutions to these
challenges. In particular, I will describe recent results on
whole-genome haplotype analysis, including haplotype inference, and the
incorporation of the HapMap data in haplotype analysis of case-control
studies. I will also discuss potential drawbacks of these methods due to
population substructure, and suggest solutions that are scalable to the
coming large-scale studies.