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NGS based haplotype assembly using matrix completion

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  • Sina Majidian
  • Mohammad Hossein Kahaei

Abstract

We apply matrix completion methods for haplotype assembly from NGS reads to develop the new HapSVT, HapNuc, and HapOPT algorithms. This is performed by applying a mathematical model to convert the reads to an incomplete matrix and estimating unknown components. This process is followed by quantizing and decoding the completed matrix in order to estimate haplotypes. These algorithms are compared to the state-of-the-art algorithms using simulated data as well as the real fosmid data. It is shown that the SNP missing rate and the haplotype block length of the proposed HapOPT are better than those of HapCUT2 with comparable accuracy in terms of reconstruction rate and switch error rate. A program implementing the proposed algorithms in MATLAB is freely available at https://github.com/smajidian/HapMC.

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  • Sina Majidian & Mohammad Hossein Kahaei, 2019. "NGS based haplotype assembly using matrix completion," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-12, March.
    • Handle: RePEc:plo:pone00:0214455
    DOI: 10.1371/journal.pone.0214455
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    Cited by:

    1. Sina Majidian & Mohammad Hossein Kahaei & Dick de Ridder, 2020. "Minimum error correction-based haplotype assembly: Considerations for long read data," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-12, June.

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