ABSTRACT
A “haplotype” is a DNA sequence that has been inherited from one parent. Each human possesses two haplotypes for most regions of the genome. The most common type of variation among haplotypes possessed by individuals in a population is the single nucleotide polymorphism (SNP), in which different nucleotides (alleles) are present at a given site (locus). Almost always, there are only two alleles at a SNP site among the individuals in a population. Given the likely complexity of trait determination, it is widely assumed that the genetic basis (if any) of important traits (e.g., diseases) can be best understood by assessing the association between the occurrence of particular haplotypes and particular traits. Hence, one of the current priorities in human genomics is the development of a full Haplotype Map of the human genome [1, 47, 48, 17], to be used in large-scale screens of populations [16, 54]. In this endeavor, a key problem is to infer haplotype pairs and/or haplotype frequencies from genotype data, since collecting haplotype data is generally more difficult than collecting genotype data. Here, we review the haplotype inference problem (inferring pairs and inferring frequencies), the major combinatorial and statistical methods proposed to solve these two problems, and the genetic models that underlie these methods.
Now that high-throughput genomic technologies are available, the dream of assessing DNA sequence variation at the population level is becoming a reality. The processes of natural selection, mutation, recombination, gene-conversion, genome rearrangements, lateral gene transfer, admixture of populations, and random drift have mixed and remixed alleles at many loci so as to create the large variety of genotypes found in many populations. The challenge is to find those genotypes that have significant and biologically meaningful associations with important traits of interest. A key technological and computational part of this challenge is to infer “haplotype information” from “genotype information”. In this section, we explain the basic biological and computational background for this “genotype to haplotype” problem.
