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Related Experiment Videos

HapCUT: an efficient and accurate algorithm for the haplotype assembly problem.

Vikas Bansal1, Vineet Bafna

  • 1Department of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0404, USA. vibansal@cs.ucsd.edu

Bioinformatics (Oxford, England)
|August 12, 2008
PubMed
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Haplotype assembly, reconstructing chromosomes from DNA fragments, is computationally challenging. Our novel HapCUT method significantly improves accuracy over existing approaches by using a graph-based combinatorial strategy.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Haplotype assembly aims to reconstruct an individual's two chromosomes from mixed DNA fragments.
  • The general problem is computationally intractable, though restricted versions have polynomial-time solutions.

Purpose of the Study:

  • To address the general haplotype assembly problem with fragments of any length and with gaps.
  • To develop a novel, accurate method for haplotype reconstruction.

Main Methods:

  • A combinatorial approach based on computing max-cuts in graphs derived from sequenced fragments.
  • Application of the HapCUT method to human genome data.

Main Results:

  • HapCUT demonstrated significantly higher accuracy (20-25% lower error correction scores) compared to greedy and Fast Hare methods.

Related Experiment Videos

  • A maximum likelihood estimator for sequence-based haplotype accuracy was developed using population data.

    • Conclusions:

    • The novel graph-based combinatorial approach offers a more accurate solution to the general haplotype assembly problem.
    • HapCUT provides a significant improvement in haplotype reconstruction accuracy.