The Supertree Toolkit 2: a new and improved software package with a Graphical User Interface for supertree construction
File(s)
Published version
Author(s)
Hill, J
Davis, KE
Type
Journal Article
Abstract
Building large supertrees involves the collection, storage, and processing of thousands of individual phylogenies to create large phylogenies with thousands to tens of thousands of taxa. Such large phylogenies are useful for macroevolutionary studies, comparative biology and in conservation and biodiversity. No easy to use and fully integrated software package currently exists to carry out this task. Here, we present a new Python-based software package that uses well defined XML schema to manage both data and metadata. It builds on previous versions by 1) including new processing steps, such as Safe Taxonomic Reduction, 2) using a user-friendly GUI that guides the user to complete at least the minimum information required and includes context-sensitive documentation, and 3) a revised storage format that integrates both tree- and meta-data into a single file. These data can then be manipulated according to a well-defined, but flexible, processing pipeline using either the GUI or a command-line based tool. Processing steps include standardising names, deleting or replacing taxa, ensuring adequate taxonomic overlap, ensuring data independence, and safe taxonomic reduction. This software has been successfully used to store and process data consisting of over 1000 trees ready for analyses using standard supertree methods. This software makes large supertree creation a much easier task and provides far greater flexibility for further work.
Date Issued
2014-03-26
Citation
Biodiversity Data Journal, 2014, 2
ISSN
1314-2828
Journal / Book Title
Biodiversity Data Journal
Volume
2
Copyright Statement
© Hill J, Davis K. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are
credited.
credited.
License URL
Description
15.04.14 KB. Ok to add published version to spiral, OA paper
Identifier
e1053
Article Number
e1053