Abstract
Recently developed MinHash-based techniques were proven successful in quickly estimating the level of similarity between large nucleotide sequences. This article discusses their usage and limitations in practice to approximating uncorrected distances between genomes, and transforming these pairwise dissimilarities into proper evolutionary distances.It is notably shown that complex distance measures can be easily approximated using simple transformation formulae based on few parameters.MinHash-based techniques can therefore be very useful for implementing fast yet accurate alignment-free phylogenetic reconstruction procedures from large sets of genomes.This last point of view is assessed with a simulation study using a dedicated bioinformatics tool.
Highlights
To estimate the level of proximity between two non-aligned genome sequences x and y, recent methods (e.g. 1–7) have focused on decomposing the two genomes into their respective sets Kx and Ky of non-duplicated nucleotide k-mers
MinHash-based p-distance approximation Varying d from 0.05 to 1.00, a total of 200 nucleotide sequence pairs with d substitution events per character were simulated under the models general time reversible (GTR) and GTR+Γ
The GTR substitution rates and the Γ shape parameters were obtained based on a maximum likelihood (ML) analysis of 142 real-case phylogenomics datasets
Summary
To estimate the level of proximity between two non-aligned genome sequences x and y, recent methods (e.g. 1–7) have focused on decomposing the two genomes into their respective sets Kx and Ky of non-duplicated nucleotide k-mers (i.e. oligonucleotides of size k). A pairwise similarity may be estimated based on the Jaccard index j = |Kx ∩ Ky| / |Kx ∪ Ky|8. The Jaccard index between two sets of k-mers is a useful measure for two main reasons. It can be quickly approximated using MinHash-based techniques (MH9), as implemented in e.g. Mash[2], sourmash[3], Dashing[4], Kmer-db[6], FastANI5, or. Such techniques select a small subset (of size σ) of hashed and sorted k-mers (called sketch) from each K and K , and x y approximate j by comparing these two subsets (for more details, see 2,9–12). The proportion p of observed differences between the two aligned genomes (often called uncorrected distance or p-distance) can be approximated from j ( without alignment) with the following formula (e.g. 13,14): p
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