block aligner
block aligner implements SIMD-accelerated sequence alignment in Rust for global and X-drop affine gap penalty alignments of nucleotide and protein sequences.
Key Features:
- Adaptive Block-Based Algorithm: Employs an adaptive block-based algorithm that greedily shifts and expands blocks of computed scores to span large gaps.
- Partial DP Computation: Computes only a fraction of the dynamic programming (DP) matrix to reduce computation compared to full DP.
- SIMD Acceleration: Leverages Single Instruction Multiple Data (SIMD) instructions to accelerate score computations.
- Performance: Demonstrates up to ninefold speed improvement over Farrar’s algorithm for protein global alignments in experimental comparisons.
- Supported Alignment Modes: Supports global alignments and X-drop affine gap penalty alignments.
- Sequence Types: Applicable to both nucleotide and protein sequence alignment.
- Implementation: Implemented as a Rust library.
- Accuracy Trade-off: Uses a greedy approximation that does not guarantee full DP optimality but shows high empirical accuracy on realistic datasets.
Scientific Applications:
- Global Alignments: Computes global sequence alignments for nucleotide and protein sequences as a faster alternative to conventional DP on realistic datasets.
- X-Drop Affine Gap Penalty Alignments: Performs X-drop affine gap penalty alignments to identify regions of similarity potentially interrupted by gaps.
Methodology:
Implements an adaptive, greedy block-based dynamic programming variant that shifts and grows blocks of scores, computes a subset of the DP matrix, and uses SIMD instructions; provided as a Rust library and supporting global and X-drop affine gap penalty alignments.
Topics
Details
- License:
- MIT
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Mac, Linux
- Added:
- 3/28/2022
- Last Updated:
- 3/28/2022
Operations
Publications
Liu D, Steinegger M. Block aligner: fast and flexible pairwise sequence alignment with SIMD-accelerated adaptive blocks. Unknown Journal. 2021. doi:10.1101/2021.11.08.467651.