ALAE: Accelerating Local Alignment with Affine Gap Exactly in Biosequence Databases
Xiaochun Yang, Honglei Liu, Bin Wang

TL;DR
ALAE is a software that significantly accelerates local alignment computations in biosequence databases by optimizing the BWT-SW algorithm with filtering and score reuse techniques, outperforming existing methods.
Contribution
This paper introduces ALAE, an efficient algorithm that speeds up exact local alignment searches using a compressed suffix array and novel filtering techniques.
Findings
ALAE achieves substantial speedup over BWT-SW.
ALAE guarantees correctness and outperforms BLAST in many scenarios.
Mathematical analysis shows predictable bounds on calculations.
Abstract
We study the problem of local alignment, which is finding pairs of similar subsequences with gaps. The problem exists in biosequence databases. BLAST is a typical software for finding local alignment based on heuristic, but could miss results. Using the Smith-Waterman algorithm, we can find all local alignments in O(mn) time, where m and n are lengths of a query and a text, respectively. A recent exact approach BWT-SW improves the complexity of the Smith-Waterman algorithm under constraints, but still much slower than BLAST. This paper takes on the challenge of designing an accurate and efficient algorithm for evaluating local-alignment searches, especially for long queries. In this paper, we propose an efficient software called ALAE to speed up BWT-SW using a compressed suffix array. ALAE utilizes a family of filtering techniques to prune meaningless calculations and an algorithm for…
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Taxonomy
TopicsAlgorithms and Data Compression · Genomics and Phylogenetic Studies · Machine Learning in Bioinformatics
