Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/57823
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Title: Bio.Phylo: A unified toolkit for processing, analyzing and visualizing phylogenetic trees in Biopython
Authors: Talevich, Eric, Invergo, Brandon M., Cock, Peter JA, Chapman, Brad A
Issue Date: 21-Aug-2012
Publisher: BioMed Central
Abstract: [Background] Ongoing innovation in phylogenetics and evolutionary biology has been accompanied by a proliferation of software tools, data formats, analytical techniques and web servers. This brings with it the challenge of integrating phylogenetic and other related biological data found in a wide variety of formats, and underlines the need for reusable software that can read, manipulate and transform this information into the various forms required to build computational pipelines.
[Results] We built a Python software library for working with phylogenetic data that is tightly integrated with Biopython, a broad-ranging toolkit for computational biology. Our library, Bio.Phylo, is highly interoperable with existing libraries, tools and standards, and is capable of parsing common file formats for phylogenetic trees, performing basic transformations and manipulations, attaching rich annotations, and visualizing trees. We unified the modules for working with the standard file formats Newick, NEXUS and phyloXML behind a consistent and simple API, providing a common set of functionality independent of the data source.
[Conclusions] Bio.Phylo meets a growing need in bioinformatics for working with heterogeneous types of phylogenetic data. By supporting interoperability with multiple file formats and leveraging existing Biopython features, this library simplifies the construction of phylogenetic workflows. We also provide examples of the benefits of building a community around a shared open-source project. Bio.Phylo is included with Biopython, available through the Biopython website, http://biopython.org.
Publisher version (URL): http://dx.doi.org/10.1186/1471-2105-13-209
URI: http://hdl.handle.net/10261/57823
ISSN: 1471-2105
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Citation: BMC Bioinformatics 13(1): 209 (2012)
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