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SHRiMP: Accurate Mapping of Short Color-space Reads

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  • Stephen M Rumble
  • Phil Lacroute
  • Adrian V Dalca
  • Marc Fiume
  • Arend Sidow
  • Michael Brudno

Abstract

The development of Next Generation Sequencing technologies, capable of sequencing hundreds of millions of short reads (25–70 bp each) in a single run, is opening the door to population genomic studies of non-model species. In this paper we present SHRiMP - the SHort Read Mapping Package: a set of algorithms and methods to map short reads to a genome, even in the presence of a large amount of polymorphism. Our method is based upon a fast read mapping technique, separate thorough alignment methods for regular letter-space as well as AB SOLiD (color-space) reads, and a statistical model for false positive hits. We use SHRiMP to map reads from a newly sequenced Ciona savignyi individual to the reference genome. We demonstrate that SHRiMP can accurately map reads to this highly polymorphic genome, while confirming high heterozygosity of C. savignyi in this second individual. SHRiMP is freely available at http://compbio.cs.toronto.edu/shrimp.Author Summary: Next Generation Sequencing (NGS) technologies are revolutionizing the way biologists acquire and analyze genomic data. NGS machines, such as Illumina/Solexa and AB SOLiD, are able to sequence genomes more cheaply by 200-fold than previous methods. One of the main application areas of NGS technologies is the discovery of genomic variation within a given species. The first step in discovering this variation is the mapping of reads sequenced from a donor individual to a known (“reference”) genome. Differences between the reference and the reads are indicative either of polymorphisms, or of sequencing errors. Since the introduction of NGS technologies, many methods have been devised for mapping reads to reference genomes. However, these algorithms often sacrifice sensitivity for fast running time. While they are successful at mapping reads from organisms that exhibit low polymorphism rates, they do not perform well at mapping reads from highly polymorphic organisms. We present a novel read mapping method, SHRiMP, that can handle much greater amounts of polymorphism. Using Ciona savignyi as our target organism, we demonstrate that our method discovers significantly more variation than other methods. Additionally, we develop color-space extensions to classical alignment algorithms, allowing us to map color-space, or “dibase”, reads generated by AB SOLiD sequencers.

Suggested Citation

  • Stephen M Rumble & Phil Lacroute & Adrian V Dalca & Marc Fiume & Arend Sidow & Michael Brudno, 2009. "SHRiMP: Accurate Mapping of Short Color-space Reads," PLOS Computational Biology, Public Library of Science, vol. 5(5), pages 1-11, May.
  • Handle: RePEc:plo:pcbi00:1000386
    DOI: 10.1371/journal.pcbi.1000386
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    Cited by:

    1. Lars Hahn & Chris-André Leimeister & Rachid Ounit & Stefano Lonardi & Burkhard Morgenstern, 2016. "rasbhari: Optimizing Spaced Seeds for Database Searching, Read Mapping and Alignment-Free Sequence Comparison," PLOS Computational Biology, Public Library of Science, vol. 12(10), pages 1-18, October.
    2. Zheng Sun & Weidong Tian, 2012. "SAP—A Sequence Mapping and Analyzing Program for Long Sequence Reads Alignment and Accurate Variants Discovery," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-6, August.
    3. Meznah Almutairy & Eric Torng, 2017. "The effects of sampling on the efficiency and accuracy of k−mer indexes: Theoretical and empirical comparisons using the human genome," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.
    4. Francesca Cordero & Marco Beccuti & Maddalena Arigoni & Susanna Donatelli & Raffaele A Calogero, 2012. "Optimizing a Massive Parallel Sequencing Workflow for Quantitative miRNA Expression Analysis," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-10, February.

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