Accelerating minimap2 for long-read sequencing applications on modern CPUs.
basic_science · Level V
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- Record sourced from PubMed, PMID 38177520.
- Also identified by DOI 10.1038/s43588-022-00201-8.
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Abstract
Long-read sequencing is now routinely used at scale for genomics and transcriptomics applications. Mapping long reads or a draft genome assembly to a reference sequence is often one of the most time-consuming steps in these applications. Here we present techniques to accelerate minimap2, a widely used software for this task. We present multiple optimizations using single-instruction multiple-data parallelization, efficient cache utilization and a learned index data structure to accelerate the three main computational modules of minimap2: seeding, chaining and pairwise sequence alignment. These optimizations result in an up to 1.8-fold reduction of end-to-end mapping time of minimap2 while maintaining identical output.