Dashing 2: genomic sketching with multiplicities and locality-sensitive hashing
Abstract
A genomic sketch is a small, probabilistic representation of the set of k-mers in a sequencing dataset. Sketches are building blocks for large-scale analyses that consider similarities between many pairs of sequences or sequence collections. While existing tools can easily compare 10,000s of genomes, relevant datasets can reach millions of sequences and beyond. Popular tools also fail to consider k-mer multiplicities, making them less applicable in quantitative settings. We describe a method called Dashing 2 that builds on the SetSketch data structure. SetSketch is related to HyperLogLog, but discards use of leading zero count in favor of a truncated logarithm of adjustable base. Unlike HLL, SetSketch can perform multiplicity-aware sketching when combined with the ProbMinHash method. Dashing 2 integrates locality-sensitive hashing to scale all-pairs comparisons to millions of sequences. Dashing 2 is free, open source software available at https://github.com/dnbaker/dashing2
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