LNETWORK

MOTIVATION: The evolutionary history of species is traditionally represented with
a rooted phylogenetic tree. Each tree comprises a set of clusters, i.e. subsets
of the species that are descended from a common ancestor. When rooted
phylogenetic trees are built from several different datasets (e.g. from different
genes), the clusters are often conflicting. These conflicting clusters cannot be
expressed as a simple phylogenetic tree; however, they can be expressed in a
phylogenetic network. Phylogenetic networks are a generalization of phylogenetic
trees that can account for processes such as hybridization, horizontal gene
transfer and recombination, which are difficult to represent in standard
tree-like models of evolutionary histories. There is currently a large body of
research aimed at developing appropriate methods for constructing phylogenetic
networks from cluster sets. The Cass algorithm can construct a much simpler
network than other available methods, but is extremely slow for large datasets or
for datasets that need lots of reticulate nodes. The networks constructed by Cass
are also greatly dependent on the order of input data, i.e. it generally derives
different phylogenetic networks for the same dataset when different input orders
are used. RESULTS: In this study, we introduce an improved Cass algorithm,
Lnetwork, which can construct a phylogenetic network for a given set of clusters.
We show that Lnetwork is significantly faster than Cass and effectively weakens
the influence of input data order. Moreover, we show that Lnetwork can construct
a much simpler network than most of the other available methods. AVAILABILITY:
Lnetwork has been built as a Java software package and is freely available at
http://nclab.hit.edu.cn/ approximately wangjuan/Lnetwork/. CONTACT:
maozuguo@hit.edu.cn SUPPLEMENTARY INFORMATION: Supplementary data are available
at Bioinformatics online.

LNETWORK: an efficient and effective method for constructing phylogenetic networks.

LNETWORK is a software tool for constructing phylogenetic networks from an input of a set of rooted phylogenetic trees.

LNETWORK

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