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

• Published in: Bioinformatics Vol. 25; no. 1; pp. 6 - 13
• Main Authors: Malhis, Nawar, Butterfield, Yaron S. N., Ester, Martin, Jones, Steven J. M.
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 01.01.2009; Oxford Publishing Limited (England)
• Subjects: Algorithms; Base Pair Mismatch; Base Sequence; Biological and medical sciences; Computational Biology; Databases, Nucleic Acid; Fundamental and applied biological sciences. Psychology; General aspects; Humans; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Original Papers; Polymorphism, Single Nucleotide - genetics; Probability; Sequence Alignment - methods; Time Factors; Information use; Probability; Maximum; Single nucleotide polymorphism; Detection; Sequence alignment
• ISSN: 1367-4803; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btn565

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