Parallel linear space algorithm for large-scale sequence alignment

Authors:
Eric Li;Cheng Xu;Tao Wang;Li Jin;Yimin Zhang
Affiliations:
Intel China Research Center, Intel Corporation, Beijing, China;Intel China Research Center, Intel Corporation, Beijing, China;Intel China Research Center, Intel Corporation, Beijing, China;Intel China Research Center, Intel Corporation, Beijing, China;Intel China Research Center, Intel Corporation, Beijing, China
Venue:
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
Year:
2005

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Abstract

Aligning long DNA sequences is a fundamental and common task in molecular biology. Though dynamic programming algorithms have been developed to solve this problem, the space and time required by these algorithms are still a challenge. In this paper we present the Parallel Linear Space Alignment (PLSA) algorithm to compute the long sequence alignment to meet this challenge. Using this algorithm, the local start points and grid cache partition the whole sequence alignment problem into several smaller independent subproblems. A novel dynamic load balancing approach then efficiently solves these subproblems in parallel, which provides more parallelism in the trace-back phase. Furthermore, PLSA helps to find k near-optimal non-intersecting alignments. Our experiments show that this proposed algorithm scales well with the increasing number of processors, and it exhibits almost linear speedup for large-scale sequences.