Bio.Phylo: A unified toolkit for processing, analyzing and visualizing phylogenetic trees in Biopython
1 Institute of Bioinformatics, University of Georgia, 120 Green Street, Athens, GA 30602, USA
2 Institute of Evolutionary Biology (CSIC-UPF), CEXS-UPF-PRBB, C/ Doctor Aiguader 88, 08003 Barcelona, Spain
3 James Hutton Institute, InvergowrieDundee DD2 5DA, UK
4 Harvard School of Public Health Bioinformatics Core, 655 Huntington Ave, Boston, MA 02115, USA
BMC Bioinformatics 2012, 13:209 doi:10.1186/1471-2105-13-209Published: 21 August 2012
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.
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.
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 webcite.