ArticleNucleic acids research2024
SigAlign: an alignment algorithm guided by explicit similarity criteria.
Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Enabling efficient and robust analysis of tandem repeats in genomic data using Wavefront-based String Decomposer.Genome research · 2026Article
- Changes in ferroptosis-related molecular expression in macrophages of community-acquired pneumonia patients and their associated with the disease progression.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025Article
- From static to dynamic: Artificial intelligence revolution in perioperative care through multimodal data fusion and closed-loop optimization.Journal of anesthesia and translational medicine · 2025Review
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2 authors.
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Abstract
In biological sequence alignment, prevailing heuristic aligners achieve high-throughput by several approximation techniques, but at the cost of sacrificing the clarity of output criteria and creating complex parameter spaces. To surmount these challenges, we introduce 'SigAlign', a novel alignment algorithm that employs two explicit cutoffs for the results: minimum length and maximum penalty per length, alongside three affine gap penalties. Comparative analyses of SigAlign against leading database search tools (BLASTn, MMseqs2) and read mappers (BWA-MEM, bowtie2, HISAT2, minimap2) highlight its performance in read mapping and database searches. Our research demonstrates that SigAlign not only provides high sensitivity with a non-heuristic approach, but also surpasses the throughput of existing heuristic aligners, particularly for high-accuracy reads or genomes with few repetitive regions. As an open-source library, SigAlign is poised to become a foundational component to provide a transparent and customizable alignment process to new analytical algorithms, tools and pipelines in bioinformatics.
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