A Parallel Pairwise Local Sequence Alignment Algorithm

Abstract

Researchers are compelled to use heuristic-based pairwise sequence alignment tools instead of Smith-Waterman (SW) algorithm due to space and time constraints, thereby losing significant amount of sensitivity. Parallelization is a possible solution, though, till date, the parallelization is restricted to database searching through database fragmentation. In this paper, the power of a cluster computer is utilized for developing a parallel algorithm, RPAlign, involving, first, the detection of regions that are potentially alignable, followed by their actual alignment. RPAlign is found to reduce the timing requirement by a factor of upto 9 and 99 when used with the basic local alignment search tool (BLAST) and SW, respectively, while keeping the sensitivity similar to the corresponding method. For distantly related sequences, which remain undetected by BLAST, RPAlign with SW can be used. Again, for megabase-scale sequences, when SW becomes computationally intractable, the proposed method can still align them reasonably fast with high sensitivity.

Shared Memory and Hardware Utilizations for the Parallelization of Local Sequences Alignment using SW Algorithm: A Review

“…Current problems of great concern in SW algorithm are computations and spaces complexity, which required powerful algorithm(s) to utilize the power of parallel machines. Implementing SW algorithm in parallel platforms plays a key role in sequences comparisons problems in order [16][17][18][19][22][23][24][25][26][27]. However, a serious weakness with this architecture is the limitation and constraint of fixed sizes of memory available for all shared processors.…”

“…Most current discussions in local sequence alignment focus on multicore architectures with shared memory such as divide and conquer techniques [16][17][18], striped SW [19][20][21][22], Instruction-set Processor (ASIP) architecture [23], data compression [24,25], genome assembly (re-sequence) algorithms [26,27], and Symmetric Multi-Processing (SMP) architecture [28,29]. This section discusses in detail these algorithms along with their advantage and disadvantage.…”

“…RPAlign algorithm is used to detect regions of similarity between two DNA or protein sequences [16]. It uses BLAST to consider regions that are potentially alienable, while SW algorithm is used for distantly related sequences.…”

Accelerating search and recognition workloads with SSE 4.2 string and text processing instructions

“…Different program of BLAST is developed for improving the performance under different applications such as [16] [17]. Some other local alignment algorithms such as RPAlign [18] were developed as fast and accurate alternatives.…”

Parallel pairwise statistical significance estimation of local sequence alignment using Message Passing Interface library

“…There exist several attempts to develop faster parallel implementations of dynamic programming‐based Smith–Waterman algorithm for sequence alignment , but these are essentially database‐searching algorithms. Apart from these, there also exists a parallel algorithm (using MPI) for alignment of a single pair of sequences , which first detects regions that are potentially alignable using frequency counts in windows, followed by their actual alignment across multiple processors. In general, there are two approaches for parallelization of Smith–Waterman algorithm: parallelization across sequence pairs (inter‐task), and parallelization within a sequence pair (intra‐task).…”