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<p>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&#xa0;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.</p>

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KegAlign: optimizing pairwise alignments with diagonal partitioning

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月17日

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  • A. Burak Gulhan,
  • Richard Burhans,
  • Robert Harris,
  • Mahmut Kandemir,
  • Maximilian Haeussler,
  • Anton Nekrutenko

摘要

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.