Work

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

Year: 2024

Type: article

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.

Source: Gigabyte

DOI: 10.46471/gigabyte.141

Authors: Peiyu Zong, Wenpeng Deng, Jian Liu, Jue Ruan

Institutions: Huazhong Agricultural University, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Ministry of Agriculture and Rural Affairs

Language: English

Topic: Genomics and Phylogenetic Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $350

Funders: Chinese Academy of Agricultural Sciences, National Key Research and Development Program of China