Haplotype reconstruction from genotype data using Imperfect Phylogeny

  • Authors:

  • Eran Halperin;Eleazar Eskin

  • Affiliations:

  • CS Division, University of California Berkeley, Berkeley, CA 92093-0114 USA;School of Computer Science and Engineering, Hebrew University, Jerusalem, 91904 Israel

  • Venue:
  • Bioinformatics
  • Year:
  • 2004

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Abstract

Critical to the understanding of the genetic basis for complex diseases is the modeling of human variation. Most of this variation can be characterized by single nucleotide polymorphisms (SNPs) which are mutations at a single nucleotide position. To characterize the genetic variation between different people, we must determine an individual's haplotype or which nucleotide base occurs at each position of these common SNPs for each chromosome. In this paper, we present results for a highly accurate method for haplotype resolution from genotype data. Our method leverages a new insight into the underlying structure of haplotypes that shows that SNPs are organized in highly correlated 'blocks'. In a few recent studies, considerable parts of the human genome were partitioned into blocks, such that the majority of the sequenced genotypes have one of about four common haplotypes in each block. Our method partitions the SNPs into blocks, and for each block, we predict the common haplotypes and each individual's haplotype. We evaluate our method over biological data. Our method predicts the common haplotypes perfectly and has a very low error rate ( Availability: The algorithm is available via a Web server at http://www.calit2.net/compbio/hap/