Dynamic Programming Algorithms for Haplotype Block Partitioning and Tag SNP Selection Using Haplotype Data or Genotype Data

摘要

Recent studies have revealed that the human genome can be decomposed into large blocks with high linkage disequilibrium (LD) and relatively limited haplotype diversity, separated by short regions of low LD. One of the practical implications of this observation is that only a small number of tag SNPs are needed for mapping genes responsible for human complex diseases, which can significantly reduce genotyping effort without much loss of power. In this paper, we survey the dynamic programming algorithms developed for haplotype block partitioning and tag SNP selection, with a focus on algorithmic considerations. Extensions of the algorithms for analysis of genotype data from unrelated individuals as well as genotype data from general pedigrees are considered. Finally, we discuss the implications of haplotype blocks and tag SNPs in association studies to search for complex disease genes.