CUSHAW: a CUDA compatible short read aligner to large genomes based on the Burrows-Wheeler transform
CUSHAW: a CUDA compatible short read aligner to large genomes based on the Burrows-Wheeler transform
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DOI：
10.1093/bioinformatics/bts276
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发表时间：
2012-07-15
期刊：
影响因子：
5.8
通讯作者：
Maskell, Douglas L.
中科院分区：
文献类型：
--
作者：
Liu, Yongchao;Schmidt, Bertil;Maskell, Douglas L.
动机：新的高通量测序技术以极低的单位成本促进了短读取的生产。短读数据集的爆炸性增长对短读数据到人类基因组等参考基因组的比对质量和执行速度提出了挑战。结果：提出了一种基于计算统一设备架构(CUDA)并行编程模型的并行化短读比对算法Cushaw。我们利用兼容CUDA的图形硬件作为加速器，以实现快速的速度。该算法采用基于Burrow-Wheeler变换(BWT)和Ferradina-Manzini索引的质量感知有界搜索方法，减少了搜索空间，获得了较高的比对质量。使用模拟和真实短读数据集进行的性能评估显示，我们的算法在一个或两个图形处理单元上运行时实现了显著的加速，而与三种流行的基于BWT的比对算法：Bowtie、BWA和SOAP2相比，对于成对端比对产生了类似甚至更好的比对质量。南瓜还在单核苷酸多态方面提供了具有竞争力的性能，需要一个大肠杆菌测试数据集。
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.