K2 and K2*: efficient alignment-free sequence similarity measurement based on Kendall statistics.

ABSTRACT:

Motivation

Alignment-free sequence comparison methods can compute the pairwise similarity between a huge number of sequences much faster than sequence-alignment based methods.

Results

We propose a new non-parametric alignment-free sequence comparison method, called K2, based on the Kendall statistics. Comparing to the other state-of-the-art alignment-free comparison methods, K2 demonstrates competitive performance in generating the phylogenetic tree, in evaluating functionally related regulatory sequences, and in computing the edit distance (similarity/dissimilarity) between sequences. Furthermore, the K2 approach is much faster than the other methods. An improved method, K2*, is also proposed, which is able to determine the appropriate algorithmic parameter (length) automat

SUBMITTER: Lin J 

PROVIDER: S-EPMC6355110 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature