Introduction

Base-calling of sequencing data produced by high-throughput sequencing platforms is a fundamental process in current bioinformatics analysis. However, existing third-party probabilistic or machine-learning methods that significantly improve the accuracy of base-calls on these platforms are impractical for production use due to their computational inefficiency.We directly formulate base-calling as a blind deconvolution problem and implemented BlindCall as an efficient solver to this inverse problem. BlindCall produced base-calls at accuracy comparable to state-of-the-art probabilistic methods while processing data at rates 10 times faster in most cases. The computational complexity of BlindCall scales linearly with read length making it better suited for new long-read sequencing technologies.

Publications

  1. BlindCall: ultra-fast base-calling of high-throughput sequencing data by blind deconvolution.
    Cite this
    Ye C, Hsiao C, Corrada Bravo H, 2014-05-01 - Bioinformatics (Oxford, England)

Credits

  1. Chengxi Ye
    Developer

    Department of Computer Science, Center for Bioinformatics and Computational Biology and Applied Mathematics and Scientific Computing, United States of America

  2. Chiaowen Hsiao
    Developer

  3. Hector Corrada Bravo
    Investigator

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Summary
AccessionBT006938
Tool TypeApplication
Category
PlatformsLinux/Unix
Technologies
User InterfaceTerminal Command Line
Download Count0
Submitted ByHector Corrada Bravo