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A Practical Exact Algorithm for the Individual Haplotyping Problem MEC/GI

  • Minzhu Xie
  • Jianxin Wang
  • Jianer Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5092)

Abstract

Given the genotype and the aligned single nucleotide polymorphism (SNP) fragments of an individual, Minimum Error Correction with Genotype Information (MEC/GI) is an important computational model to infer a pair of haplotypes compatible with the genotype by correcting minimum number of SNPs in the given SNP fragments. For the problem, there has been no practical exact algorithm. In DNA sequencing experiments, due to technical limits, the maximum length of a fragment sequenced directly is about 1kb. In consequence, the maximum number k of SNP sites that a fragment covers is usually small (usually smaller than 10). Based on the observation above, the current paper introduces a new parameterized dynamic programming algorithm of running time O(m k 2 k  + mlogm + mk), where m is the number of fragments. The algorithm solves the MEC/GI problem efficiently even if the number of fragments and SNPs are large, and is practical in real biological applications.

Keywords

Single Nucleotide Polymorphism Reconstruction Rate Haplotype Inference Single Nucleotide Polymorphism Site Haplotype Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Minzhu Xie
    • 1
    • 2
  • Jianxin Wang
    • 1
  • Jianer Chen
    • 1
    • 3
  1. 1.School of Information Science and EngineeringCentral South UniversityChangshaP.R. China
  2. 2.College of Physics and Information ScienceHunan Normal UniversityChangshaP.R. China
  3. 3.Department of Computer ScienceTexas A&M UniversityUSA

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