Abstract
MotivationTo obtain large-scale sequence alignments in a fast and flexible way is an important step in the analyses of next generation sequencing data. Applications based on the Smith-Waterman (SW) algorithm are often either not fast enough, limited to dedicated tasks or not sufficiently accurate due to statistical issues. Current SW implementations that run on graphics hardware do not report the alignment details necessary for further analysis.ResultsWith the Parallel SW Alignment Software (PaSWAS) it is possible (a) to have easy access to the computational power of NVIDIA-based general purpose graphics processing units (GPGPUs) to perform high-speed sequence alignments, and (b) retrieve relevant information such as score, number of gaps and mismatches. The software reports multiple hits per alignment. The added value of the new SW implementation is demonstrated with two test cases: (1) tag recovery in next generation sequence data and (2) isotype assignment within an immunoglobulin 454 sequence data set. Both cases show the usability and versatility of the new parallel Smith-Waterman implementation.
Highlights
Available generation sequencing platforms [1] produce millions of short reads, from 30 bases up to several hundred bases, which are analyzed for single-nucleotide polymorphisms (SNPs) [2], miRNAs [3] and other short sequences, or used for purposes such as whole genomesequencing [4]
We show how the results of Parallel Smith-Waterman Alignment Software (PaSWAS) compare to the BLAST-based analysis that were routinely performed at the institutes involved (S1 Text)
In this paper we present PaSWAS as novel parallel implementation of the SW algorithm on a graphics processing unit (GPU)
Summary
Available generation sequencing platforms [1] produce millions of short reads, from 30 bases up to several hundred bases, which are analyzed for SNPs [2], miRNAs [3] and other short sequences, or used for purposes such as whole genome (re)sequencing [4]. Flexible and highly accurate alignment software is an important tool for analyzing such sequencing data. The alignment software should be able to process the large amounts of data within a limited timeframe, preferably on low cost and high-speed hardware. The software needs to be highly accurate, giving the exact locations of mismatches, gaps, etc. It is important that the application is flexible, so it can be used for many different purposes.
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