TSTA: thread and SIMD-based trapezoidal pairwise/multiple sequence-alignment method
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.
Authors
- J. Liu (ORCID: https://orcid.org/0000-0001-6726-3268)
- Peiyu Zong
- Jue Ruan (ORCID: https://orcid.org/0000-0003-3713-3192)
- Wenpeng Deng
Institutions
- Huazhong Agricultural University (CN)
- Agricultural Genomics Institute at Shenzhen (CN)
- Chinese Academy of Agricultural Sciences (CN)
- Ministry of Agriculture and Rural Affairs (CN)
Publication Details
- Journal
- Gigabyte
- Published
- 2024-11-05
- DOI
- https://doi.org/10.46471/gigabyte.141
- Citations
- 1
- Primary Topic
- Genomics and Phylogenetic Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.23
Funders
- Chinese Academy of Agricultural Sciences
- National Key Research and Development Program of China