Journal
BIOINFORMATICS
Volume 34, Issue 10, Pages 1682-1689Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btx809
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Funding
- Chinese National Natural Science Foundation [61472082]
- Natural Science Foundation of Fujian Province of China [2014J01220]
- US National Science Foundation [IIS-1552860]
- Scientific Research Innovation Team Construction Program of Fujian Normal University [IRTL1702]
- NATIONAL CANCER INSTITUTE [P30CA086862] Funding Source: NIH RePORTER
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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 K-2, based on the Kendall statistics. Comparing to the other state-of-the-art alignment-free comparison methods, K-2 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 K-2 approach is much faster than the other methods. An improved method, K-2*, is also proposed, which is able to determine the appropriate algorithmic parameter (length) automatically, without first considering different values. Comparative analysis with the state-of-the-art alignment-free sequence similarity methods demonstrates the superiority of the proposed approaches, especially with increasing sequence length, or increasing dataset sizes.
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