Table 1. Summary of genetic distances used to infer the relationships among samples.

Class	Distance	Description
Site-based	NUCmer	Suffix array method to efficiently perform pairwise whole-genome alignment
	Extended MLST	Employs the Basic Local Alignment Search Tool to perform pairwise comparisons of predicted open reading frames
k-mer based	Jaccard Distance	1 –Jaccard index (i.e., the intersection divided by the union of all k-mers found between two samples)
	Manhattan Distance	Sum of the absolute differences between the abundance of each k-mer present between two samples
	Euclidean Distance	The square root of the sum of square of all pairwise differences in k-mer abundance
	Mash Distance	Employs the MinHash [23] technique to reduce genomes to sketches (i.e., a reduced representation of the information within the sequence data) and estimates a novel evolutionary distance metric among them
	Mash Jaccard Distance	The Jaccard Distance (as described above) but based on the sketch size (e.g., the number of hashes)