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ETE: a python Environment for Tree Exploration
by
Huerta-Cepas, Jaime
, Gabaldón, Toni
, Dopazo, Joaquín
in
Algorithms
/ Bioinformatics
/ Biomedical and Life Sciences
/ Computational biology
/ Computational Biology - methods
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Databases, Genetic
/ Information management
/ Life Sciences
/ Microarrays
/ Phylogenetic trees
/ Phylogeny
/ Python (Programming language)
/ Software
2010
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ETE: a python Environment for Tree Exploration
by
Huerta-Cepas, Jaime
, Gabaldón, Toni
, Dopazo, Joaquín
in
Algorithms
/ Bioinformatics
/ Biomedical and Life Sciences
/ Computational biology
/ Computational Biology - methods
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Databases, Genetic
/ Information management
/ Life Sciences
/ Microarrays
/ Phylogenetic trees
/ Phylogeny
/ Python (Programming language)
/ Software
2010
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Do you wish to request the book?
ETE: a python Environment for Tree Exploration
by
Huerta-Cepas, Jaime
, Gabaldón, Toni
, Dopazo, Joaquín
in
Algorithms
/ Bioinformatics
/ Biomedical and Life Sciences
/ Computational biology
/ Computational Biology - methods
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Databases, Genetic
/ Information management
/ Life Sciences
/ Microarrays
/ Phylogenetic trees
/ Phylogeny
/ Python (Programming language)
/ Software
2010
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Journal Article
ETE: a python Environment for Tree Exploration
2010
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Overview
Background
Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale.
Results
Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be used to automate the graphical rendering of trees with customized node-specific visualizations.
Conclusions
ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from
http://ete.cgenomics.org
.
Publisher
BioMed Central,BioMed Central Ltd,BMC
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