In:
Bioinformatics, Oxford University Press (OUP), Vol. 28, No. 14 ( 2012-07-15), p. 1830-1837
Abstract:
Motivation: New high-throughput sequencing technologies have promoted the production of short reads with dramatically low unit cost. The explosive growth of short read datasets poses a challenge to the mapping of short reads to reference genomes, such as the human genome, in terms of alignment quality and execution speed. Results: We present CUSHAW, a parallelized short read aligner based on the compute unified device architecture (CUDA) parallel programming model. We exploit CUDA-compatible graphics hardware as accelerators to achieve fast speed. Our algorithm uses a quality-aware bounded search approach based on the Burrows–Wheeler transform (BWT) and the Ferragina–Manzini index to reduce the search space and achieve high alignment quality. Performance evaluation, using simulated as well as real short read datasets, reveals that our algorithm running on one or two graphics processing units achieves significant speedups in terms of execution time, while yielding comparable or even better alignment quality for paired-end alignments compared with three popular BWT-based aligners: Bowtie, BWA and SOAP2. CUSHAW also delivers competitive performance in terms of single-nucleotide polymorphism calling for an Escherichia coli test dataset. Availability: http://cushaw.sourceforge.net. Contact: liuy@uni-mainz.de; bertil.schmidt@uni-mainz.de Supplementary information: Supplementary data are available at Bioinformatics online.
Type of Medium:
Online Resource
ISSN:
1367-4811
,
1367-4803
DOI:
10.1093/bioinformatics/bts276
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2012
detail.hit.zdb_id:
1468345-3
SSG:
12
