ArticleGigaByte (Hong Kong, China)2026
Efficient downsampling of genome alignments with Rasusa.
Article in GigaByte (Hong Kong, China), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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3 authors.
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Abstract
High-throughput sequencing datasets frequently exhibit extreme read depth variation, biasing downstream analysis. Normalising coverage to a specific depth cap is important, yet existing tools rely on computationally expensive fetch-based or non-deterministic greedy algorithms. Here, we present a new coordinate-sorted sweep-line algorithm implemented in the open-source software rasusa that enforces a strict coverage cap at every genomic position. By utilising seeded random priority assignment, we achieve unbiased, reproducible read selection. The algorithm reduces runtimes by over 1,400-fold compared to legacy fetch-based methods-slashing processing from hours to mere seconds-and operates roughly four times faster than VariantBam. Furthermore, it requires only 8 MB of memory for long-read data. This provides a highly efficient, scalable, and reproducible solution for sequencing coverage normalisation.
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