PT - JOURNAL ARTICLE AU - Richard Wilton AU - Tamas Budavari AU - Ben Langmead AU - Sarah Wheelan AU - Steven L. Salzberg AU - Alex Szalay TI - Faster sequence alignment through GPU-accelerated restriction of the seed-and-extend search space AID - 10.1101/007641 DP - 2014 Jan 01 TA - bioRxiv PG - 007641 4099 - http://biorxiv.org/content/early/2014/08/01/007641.short 4100 - http://biorxiv.org/content/early/2014/08/01/007641.full AB - Motivation In computing pairwise alignments of biological sequences, software implementations employ a variety of heuristics that decrease the computational effort involved in computing potential alignments. A key element in achieving high processing throughput is to identify and prioritize potential alignments where high-scoring mappings can be expected. These tasks involve listprocessing operations that can be efficiently performed on GPU hardware.Results We implemented a read aligner called A21 that exploits GPU-based parallel sort and reduction techniques to restrict the number of locations where potential alignments may be found. When compared with other high-throughput aligners, this approach finds more high-scoring mappings without sacrificing speed or accuracy. A21 running on a single GPU is about 10 times faster than comparable CPU-based tools; it is also faster and more sensitive in comparison with other recent GPU-based aligners.Availability The A21 software is open source and available at https://github.com/RWilton/A21.Contact rwilton{at}pha.jhu.eduSupplementary information Supplementary results are available at <<<TBD>>>