Introduction

Accurate haplotyping-determining from which parent particular portions of the genome are inherited-is still mostly an unresolved problem in genomics. This problem has only recently started to become tractable, thanks to the development of new long read sequencing technologies. Here, we introduce ProbHap, a haplotyping algorithm targeted at such technologies. The main algorithmic idea of ProbHap is a new dynamic programming algorithm that exactly optimizes a likelihood function specified by a probabilistic graphical model and which generalizes a popular objective called the minimum error correction. In addition to being accurate, ProbHap also provides confidence scores at phased positions.On a standard benchmark dataset, ProbHap makes 11% fewer errors than current state-of-the-art methods. This accuracy can be further increased by excluding low-confidence positions, at the cost of a small drop in haplotype completeness.Our source code is freely available at: https://github.com/kuleshov/ProbHap.

Publications

  1. Probabilistic single-individual haplotyping.
    Cite this
    Kuleshov V, 2014-09-01 - Bioinformatics (Oxford, England)

Credits

  1. Volodymyr Kuleshov
    Investigator

    Department of Computer Science, Stanford University, United States of America

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Summary
AccessionBT000027
Tool TypeApplication
Category
PlatformsLinux/Unix
Technologies
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByVolodymyr Kuleshov