Abstract

With few exceptions, current methods for short read mapping make use of simple seed heuristics to speed up the search. Most of the underlying matching models neglect the necessity to allow not only mismatches, but also insertions and deletions. Current evaluations indicate, however, that very different error models apply to the novel high-throughput sequencing methods. While the most frequent error-type in Illumina reads are mismatches, reads produced by 454's GS FLX predominantly contain insertions and deletions (indels). Even though 454 sequencers are able to produce longer reads, the method is frequently applied to small RNA (miRNA and siRNA) sequencing. Fast and accurate matching in particular of short reads with diverse errors is therefore a pressing practical problem. We introduce a matching model for short reads that can, besides mismatches, also cope with indels. It addresses different error models. For example, it can handle the problem of leading and trailing contaminations caused by primers and poly-A tails in transcriptomics or the length-dependent increase of error rates. In these contexts, it thus simplifies the tedious and error-prone trimming step. For efficient searches, our method utilizes index structures in the form of enhanced suffix arrays. In a comparison with current methods for short read mapping, the presented approach shows significantly increased performance not only for 454 reads, but also for Illumina reads. Our approach is implemented in the software segemehl available at http://www.bioinf.uni-leipzig.de/Software/segemehl/.

Highlights

  • Since the 454 pyrosequencing technology [3] has been introduced to the market, the need for algorithms that efficiently map huge amounts of reads to reference genomes has rapidly increased

  • The successful mapping of high-throughput sequencing (HTS) reads to reference genomes largely depends on the accuracy of both the sequencing technologies and reference genomes

  • We have developed and implemented a new approach for short read mapping that, in a first step, computes exact matches of the read and the reference genome

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Summary

Introduction

Since the 454 pyrosequencing technology [3] has been introduced to the market, the need for algorithms that efficiently map huge amounts of reads to reference genomes has rapidly increased. The development of read mapping methods decisively depends on specifications and error models of the respective technologies. Available read mapping programs are designed to allow for mismatches when aligning the reads to the reference genome. E.g. MAQ [7], SOAP [8], SHRiMP [9] or ELAND (proprietary), use seeding techniques that gain their speed from pre-computed hash look-up tables. Some of these programs, in particular SOAP and MAQ, are designed to map short Illumina or SOLiD reads. PatMaN [12] and BWA [13] are able to handle a limited number of indels

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