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KegAlign: optimizing pairwise alignments with diagonal partitioning
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DOI：10.1186/s13059-025-03830-0.png)
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Abstract
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Advances in sequencing and assembly allow the creation of thousands of genome assemblies. However, producing multiple alignments required for their analysis lags behind due to the time-consuming process of pairwise alignment, typically performed by the slow but sensitive tool lastZ. Here, we develop KegAlign, an optimized GPU-enabled pairwise aligner. KegAlign employs a novel diagonal partitioning parallelization strategy and leverages advanced GPU features. It can compute a human/mouse alignment in under 6 h on a GPU-containing node without pre-partitioning, maintaining lastZ-level sensitivity crucial for divergent genomes. KegAlign is available as source code, a Conda package, and a user-friendly Galaxy workflow.
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