Dataset Information

TreeKO: a duplication-aware algorithm for the comparison of phylogenetic trees.

ABSTRACT: Comparisons of tree topologies provide relevant information in evolutionary studies. Most existing methods share the drawback of requiring a complete and exact mapping of terminal nodes between the compared trees. This severely limits the scope of genome-wide analyses, since trees containing duplications are pruned arbitrarily or discarded. To overcome this, we have developed treeKO, an algorithm that enables the comparison of tree topologies, even in the presence of duplication and loss events. To do so treeKO recursively splits gene trees into pruned trees containing only orthologs to subsequently compute a distance based on the combined analyses of all pruned tree comparisons. In addition treeKO, implements the possibility of computing phylome support values, and reconciliation-based measures such as the number of inferred duplication and loss events.

SUBMITTER: Marcet-Houben M

PROVIDER: S-EPMC3105381 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

TreeKO: a duplication-aware algorithm for the comparison of phylogenetic trees.

Marcet-Houben Marina M Gabaldón Toni T

Nucleic acids research 20110218 10

Comparisons of tree topologies provide relevant information in evolutionary studies. Most existing methods share the drawback of requiring a complete and exact mapping of terminal nodes between the compared trees. This severely limits the scope of genome-wide analyses, since trees containing duplications are pruned arbitrarily or discarded. To overcome this, we have developed treeKO, an algorithm that enables the comparison of tree topologies, even in the presence of duplication and loss events. ...[more]

PMID: 21335609

Similar Datasets

Project description:Phylogenetic analysis is used to analyze the evolution of species according to the characteristics of biological sequences. The analytical results are generally represented by phylogenetic trees. NJ (neighbor joining) is a frequently used algorithm for constructing phylogenetic trees because of its few assumptions, fast operation, and high accuracy, and is based on the distance between taxa. It is known that NJ usually constructs different phylogenetic trees for the same dataset with differences in input order, which are known as “tied trees.” This article proposes an improved method of NJ, called ENJ (extended neighbor joining). The ENJ can join several (currently limited to three) nodes with the same minimum distance into a new node, rather than joining two nodes in one iteration, so it can construct triple phylogenetic trees. We have inferred the formulas for updating the distance values and calculating the branch lengths for the ENJ algorithm. We have tested the ENJ with simulated and real data. The experimental results show that, compared with other methods, the trees constructed by the ENJ have greater similarity to the initial trees, and the ENJ is much faster than the NJ algorithm. Moreover, we have constructed a phylogenetic tree for the novel coronavirus (COVID-19) and related coronaviruses by ENJ, which shows that COVID-19 and SARS-CoV are closer than other coronaviruses. Because it differs from the existing phylogenetic trees for those coronaviruses, we constructed a phylogenetic network for them. The network shows those species have had a reticulate evolution. Graphical Abstract Accurately inferring evolutionary relationships between species can help humans to understand the evolutionary history and the mechanism. ENJ is an efficient and effective algorithm for constructing phylogenetic trees, which can construct triple phylogenetic trees, if necessary. The trees constructed by ENJ can better describe the original information and reflect the real evolutionary relationship of species.

Dataset Information

TreeKO: a duplication-aware algorithm for the comparison of phylogenetic trees.

Publications

TreeKO: a duplication-aware algorithm for the comparison of phylogenetic trees.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets