TSTA: thread and SIMD-based trapezoidal pairwise/multiple sequence-alignment method.

Abstract

The rapid advancements in sequencing length necessitate the adoption of increasingly efficient sequence alignment algorithms. The Needleman-Wunsch method introduces the foundational dynamic-programming 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 and implementation: Source codes are available at https://github.com/bxskdh/TSTA.