Single Molecule Real-Time (SMRT) sequencing is one of the popular issues in third-generation sequencing technology. Compared with next-generation sequencing technology, SMRT can detect single molecules and has much longer read lengths, which also leads to a huge increase in the amount of data. As the performance of a single CPU has reached its bottleneck, single-node computing is far from meeting the SMRT sequencing requirements. An alternative solution is parallel computing. It makes the alignment algorithm run on multiple computing nodes, thus greatly decreases the running time. The Regional Hashing-based Alignment Tool (rHAT) is a novel approach developed especially for SMRT sequencing. It has better sensitivity, improved correctness compared with existing sequence alignment tools. However, the original rHAT source can only run on a single node, which dramatically limits its performance. In this article, we developed PrHAT, a parallel sequence alignment version of rHAT. We test PrHAT on simulated and real datasets which the original rHAT used. Our results show that PrHAT reduces the computing wall-time from nearly an hour to several minutes. In the process of increasing the number of nodes from 2 to 16 on aligning large-scale datasets, PrHAT achieves speedups of 1.94–14.87x. The parallel efficiency decreases from 97% to 93%; moreover, its weak scaling remains almost unchanged. Based on PrHAT, we developed OpenPrHAT. It has a similar performance towards PrHAT, but can run on other computing devices like GPU in the platform. We expect that the implementation of PrHAT will promote the development of SMRT in third-generation sequencing technology.
原文链接
分享
引用
