Inferring phylogenies of evolving sequences without multiple sequence alignment

Chan, Cheong Xin, Bernard, Guillaume, Poirion, Olivier, Hogan, James M. and Ragan, Mark A. (2014) Inferring phylogenies of evolving sequences without multiple sequence alignment. Scientific Reports, 4 e6504.1-e6504.9. doi:10.1038/srep06504

Author Chan, Cheong Xin
Bernard, Guillaume
Poirion, Olivier
Hogan, James M.
Ragan, Mark A.
Title Inferring phylogenies of evolving sequences without multiple sequence alignment
Journal name Scientific Reports   Check publisher's open access policy
ISSN 2045-2322
Publication date 2014-09
Sub-type Article (original research)
DOI 10.1038/srep06504
Open Access Status DOI
Volume 4
Start page e6504.1
End page e6504.9
Total pages 9
Place of publication London United Kingdom
Publisher Nature Publishing Group
Collection year 2015
Language eng
Formatted abstract
Alignment-free methods, in which shared properties of sub-sequences (e.g. identity or match length) are extracted and used to compute a distance matrix, have recently been explored for phylogenetic inference. However, the scalability and robustness of these methods to key evolutionary processes remain to be investigated. Here, using simulated sequence sets of various sizes in both nucleotides and amino acids, we systematically assess the accuracy of phylogenetic inference using an alignment-free approach, based on D2 statistics, under different evolutionary scenarios. We find that compared to a multiple sequence alignment approach, D2 methods are more robust against among-site rate heterogeneity, compositional biases, genetic rearrangements and insertions/deletions, but are more sensitive to recent sequence divergence and sequence truncation. Across diverse empirical datasets, the alignment-free methods perform well for sequences sharing low divergence, at greater computation speed. Our findings provide strong evidence for the scalability and the potential use of alignment-free methods in large-scale phylogenomics.
Keyword Approximate word matches
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
Institute for Molecular Bioscience - Publications
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Citation counts: TR Web of Science Citation Count  Cited 8 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 7 times in Scopus Article | Citations
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