6 research outputs found
A Perl Package and an Alignment Tool for Phylogenetic Networks
Phylogenetic networks are a generalization of phylogenetic trees that allow
for the representation of evolutionary events acting at the population level,
like recombination between genes, hybridization between lineages, and lateral
gene transfer. While most phylogenetics tools implement a wide range of
algorithms on phylogenetic trees, there exist only a few applications to work
with phylogenetic networks, and there are no open-source libraries either.
In order to improve this situation, we have developed a Perl package that
relies on the BioPerl bundle and implements many algorithms on phylogenetic
networks. We have also developed a Java applet that makes use of the
aforementioned Perl package and allows the user to make simple experiments with
phylogenetic networks without having to develop a program or Perl script by
herself.
The Perl package has been accepted as part of the BioPerl bundle. It can be
downloaded from http://dmi.uib.es/~gcardona/BioInfo/Bio-PhyloNetwork.tgz. The
web-based application is available at http://dmi.uib.es/~gcardona/BioInfo/. The
Perl package includes full documentation of all its features.Comment: 5 page
Characterization of Reticulate Networks Based on the Coalescent with Recombination
Phylogenetic networks aim to represent the evolutionary history of taxa. Within these, reticulate networks are explicitly able to accommodate evolutionary events like recombination, hybridization, or lateral gene transfer. Although several metrics exist to compare phylogenetic networks, they make several assumptions regarding the nature of the networks that are not likely to be fulfilled by the evolutionary process. In order to characterize the potential disagreement between the algorithms and the biology, we have used the coalescent with recombination to build the type of networks produced by reticulate evolution and classified them as regular, tree sibling, tree child, or galled trees. We show that, as expected, the complexity of these reticulate networks is a function of the population recombination rate. At small recombination rates, most of the networks produced are already more complex than regular or tree sibling networks, whereas with moderate and large recombination rates, no network fit into any of the standard classes. We conclude that new metrics still need to be devised in order to properly compare two phylogenetic networks that have arisen from reticulating evolutionary process
Characterization of phylogenetic networks with NetTest
<p>Abstract</p> <p>Background</p> <p>Typical evolutionary events like recombination, hybridization or gene transfer make necessary the use of phylogenetic networks to properly depict the evolution of DNA and protein sequences. Although several theoretical classes have been proposed to characterize these networks, they make stringent assumptions that will likely not be met by the evolutionary process. We have recently shown that the complexity of simulated networks is a function of the population recombination rate, and that at moderate and large recombination rates the resulting networks cannot be categorized. However, we do not know whether these results extend to networks estimated from real data.</p> <p>Results</p> <p>We introduce a web server for the categorization of explicit phylogenetic networks, including the most relevant theoretical classes developed so far. Using this tool, we analyzed statistical parsimony phylogenetic networks estimated from ~5,000 DNA alignments, obtained from the NCBI PopSet and Polymorphix databases. The level of characterization was correlated to nucleotide diversity, and a high proportion of the networks derived from these data sets could be formally characterized.</p> <p>Conclusions</p> <p>We have developed a public web server, <it>NetTest </it>(freely available from the software section at <url>http://darwin.uvigo.es</url>), to formally characterize the complexity of phylogenetic networks. Using NetTest we found that most statistical parsimony networks estimated with the program TCS could be assigned to a known network class. The level of network characterization was correlated to nucleotide diversity and dependent upon the intra/interspecific levels, although no significant differences were detected among genes. More research on the properties of phylogenetic networks is clearly needed.</p