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Faster sequence alignment through GPU-accelerated restriction of the seed-and-extend search space  

2014-08-04 11:44:18|  分类: 生物信息分析 |  标签: |举报 |字号 订阅

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Richard Wilton, Tamas Budavari, Ben Langmead, Sarah J Wheelan, Steven Salzberg, AlexSzalay
doi: http://dx.doi.org/10.1101/007641
ABSTRACT
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 list-processing 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.

 

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