Mash: fast genome and metagenome distance estimation using MinHash. Mash extends the MinHash dimensionality-reduction technique to include a pairwise mutation distance and P value significance test, enabling the efficient clustering and search of massive sequence collections. Mash reduces large sequences and sequence sets to small, representative sketches, from which global mutation distances can be rapidly estimated. We demonstrate several use cases, including the clustering of all 54,118 NCBI RefSeq genomes in 33 CPU h; real-time database search using assembled or unassembled Illumina, Pacific Biosciences, and Oxford Nanopore data; and the scalable clustering of hundreds of metagenomic samples by composition. Mash is freely released under a BSD license (https://github.com/marbl/mash).
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Koslicki, David; Zabeti, Hooman: Improving MinHash via the containment index with applications to metagenomic analysis (2019)
- Sahlin, Kristoffer; Medvedev, Paul: \textitDenovo clustering of long-read transcriptome data using a greedy, quality-value based algorithm (2019)