A general and extensible algorithmic framework for biological sequence alignment across scales and applications
Year: 2026
Type: preprint
Abstract: Sequence alignment underlies nearly every facet of modern genomics, from genetic testing and cancer profiling to functional genome annotation. Yet, despite decades of algorithmic innovation, most existing aligners remain narrowly optimized for specific tasks, leading to fragmented analytical workflows. Here, we introduce the Versatile Alignment Toolkit (VAT), a unified algorithmic framework that brings together diverse seeding and genome-indexing strategies within a single, modulated architecture. VAT features a novel multi-view k-mer indexing scheme that integrates multiple seeding strategies, while enabling run-time adjustment of seed length without re-indexing. A hardware-efficient bitonic sort algorithm accelerates multi-view table construction, ensuring scalability across large datasets. VAT delivers consistently high alignment quality and efficiency across a wide range of alignment tasks, including short- and long-read mapping, homology search, and whole-genome alignment. By bridging alignment paradigms that were previously treated in isolation, VAT reduces workflow complexity and establishes an extensible foundation for future sequencing technologies.
Source: Research Square
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7161139065