Parallel divide and conquer bio-sequence comparison based on Smith-Waterman algorithm

Biological sequence (e.g. DNA sequence) can be treated as strings over some fixed alphabet of characters (a, c, t and g)1]. Sequence alignment is a procedure of comparing two or more sequences by searching for a series of individual characters that are in the same order in the sequences. Two-sequence alignment, pair-wise alignment, is a way of stacking one sequence above the other and matching characters from the two sequences thaat lie in the same column: identical characters are placed in …

Parallel divide and conquer bio-sequence comparison based on smith-waterman algorithm

Tools for pair-wise bio-sequence alignment have for long played a central role in computation biology. Several algorithms for bio-sequence alignment have been developed. The Smith-Waterman algorithm, based on dynamic programming, is considered the most fundamental alignment algorithm in bioinformatics. However the existing parallel Smith-Waterman algorithm needs large memory space, and this disadvantage limits the size of a sequence to be handled. As the data of biological sequences expand rapidly, the memory requirement of the existing parallel Smith- Waterman algorithm has become a critical problem. For solving this problem, we develop a new parallel bio-sequence alignment algorithm, using the strategy of divide and conquer, named PSW-DC algorithm. In our algorithm, first, we partition the query sequence into several subsequences and distribute them to every processor respectively, then compare each subsequence with the whole subject sequence in parallel, using the Smith-Waterman algorithm, and get an interim result, finally obtain the optimal alignment between the query sequence and subject sequence, through the special combination and extension method. Memory space required in our algorithm is reduced significantly in comparison with existing ones. We also develop a key technique of combination and extension, named the C&E method, to manipulate the interim results and obtain the final sequences alignment. We implement the new parallel bio-sequences alignment algorithm, the PSW-DC, in a cluster parallel system.