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Bioinformatics Advance Access originally published online on October 30, 2008
Bioinformatics 2009 25(1):6-13; doi:10.1093/bioinformatics/btn565
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Slider—maximum use of probability information for alignment of short sequence reads and SNP detection

Nawar Malhis 1,*, Yaron S. N. Butterfield 1, Martin Ester 2 and Steven J. M. Jones 1

1Genome Sciences Centre, BC Cancer Agency, Vancouver and 2School of Computing Science, Simon Fraser University, Burnaby, BC, Canada

*To whom correspondence should be addressed.


  Abstract

Motivation: A plethora of alignment tools have been created that are designed to best fit different types of alignment conditions. While some of these are made for aligning Illumina Sequence Analyzer reads, none of these are fully utilizing its probability (prb) output. In this article, we will introduce a new alignment approach (Slider) that reduces the alignment problem space by utilizing each read base's probabilities given in the prb files.

Results: Compared with other aligners, Slider has higher alignment accuracy and efficiency. In addition, given that Slider matches bases with probabilities other than the most probable, it significantly reduces the percentage of base mismatches. The result is that its SNP predictions are more accurate than other SNP prediction approaches used today that start from the most probable sequence, including those using base quality.

Contact: nmalhis{at}bcgsc.ca

Supplementary information and availability: http://www.bcgsc.ca/platform/bioinfo/software/slider

Associate Editor: Dmitrij Frishman

Received on July 15, 2008; revised on October 27, 2008; accepted on October 27, 2008

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