title: Slider--maximum use of probability information for alignment of short sequence reads and SNP detection.
abstract: BACKGROUND
  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.
authors.affiliation: Genome Sciences Centre, BC Cancer Agency, Vancouver and School of Computing Science, Simon Fraser University, Burnaby, BC, Canada.
authors.forename: Nawar
authors.initials: N
authors.lastname: Malhis
authors.forename: Yaron S N
authors.initials: YS
authors.lastname: Butterfield
authors.forename: Martin
authors.initials: M
authors.lastname: Ester
authors.forename: Steven J M
authors.initials: SJ
authors.lastname: Jones
mesh_terms: D000465:Algorithms; D020137:Base Pair Mismatch; D001483:Base Sequence; D019295:Computational Biology; D030561:Databases, Nucleic Acid; D006801:Humans; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D011336:Probability; D016415:Sequence Alignment / Q000379:methods*; D013997:Time Factors