Inferring phylogenies of evolving sequences without multiple sequence alignment
Identifieur interne : 003806 ( Main/Exploration ); précédent : 003805; suivant : 003807Inferring phylogenies of evolving sequences without multiple sequence alignment
Auteurs : Cheong Xin Chan [Australie] ; Guillaume Bernard [Australie] ; Olivier Poirion [Australie, France] ; James M. Hogan [Australie] ; Mark A. Ragan [Australie]Source :
- Scientific Reports [ 2045-2322 ] ; 2014.
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
Url:
DOI: 10.1038/srep06504
PubMed: 25266120
PubMed Central: 4179140
Affiliations:
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<front><div type="abstract" xml:lang="en"><p>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 <italic>D<sub>2</sub>
</italic>
statistics, under different evolutionary scenarios. We find that compared to a multiple sequence alignment approach, <italic>D<sub>2</sub>
</italic>
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.</p>
</div>
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<affiliations><list><country><li>Australie</li>
<li>France</li>
</country>
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<tree><country name="Australie"><noRegion><name sortKey="Chan, Cheong Xin" sort="Chan, Cheong Xin" uniqKey="Chan C" first="Cheong Xin" last="Chan">Cheong Xin Chan</name>
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<name sortKey="Bernard, Guillaume" sort="Bernard, Guillaume" uniqKey="Bernard G" first="Guillaume" last="Bernard">Guillaume Bernard</name>
<name sortKey="Hogan, James M" sort="Hogan, James M" uniqKey="Hogan J" first="James M." last="Hogan">James M. Hogan</name>
<name sortKey="Poirion, Olivier" sort="Poirion, Olivier" uniqKey="Poirion O" first="Olivier" last="Poirion">Olivier Poirion</name>
<name sortKey="Ragan, Mark A" sort="Ragan, Mark A" uniqKey="Ragan M" first="Mark A." last="Ragan">Mark A. Ragan</name>
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<country name="France"><noRegion><name sortKey="Poirion, Olivier" sort="Poirion, Olivier" uniqKey="Poirion O" first="Olivier" last="Poirion">Olivier Poirion</name>
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</record>
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