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bioRxiv · 10.1101/2024.09.18.613655

TSTA: Thread and SIMD-Based Trapezoidal Pairwise/Multiple Sequence Alignment Method

Peiyu, Z.·Liu, J.·Deng, W.·Ruan, J.
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Abstract

AbstractsThe rapid advancements in sequencing length necessitate the adoption of increasingly efficient sequence alignment algorithms. The Needleman-Wunsch method introduces the foundational dynamic programming (DP) matrix calculation for global alignment, which evaluates the overall alignment of sequences. However, this method is known to be highly time-consuming. The proposed TSTA algorithm leverages both vector-level and thread-level parallelism to accelerate pairwise and multiple sequence alignments. Availability & ImplementationSource code are available at https://github.com/bxskdh/TSTA.

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Peiyu, Z., Liu, J., Deng, W., Ruan, J.. 2024-09-22. TSTA: Thread and SIMD-Based Trapezoidal Pairwise/Multiple Sequence Alignment Method. https://doi.org/10.1101/2024.09.18.613655

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