SPECTRE: a Suite of PhylogEnetiC Tools for Reticulate Evolution

Bastkowski, Sarah, Mapleson, Daniel, Spillner, Andreas, Wu, Taoyang ORCID: https://orcid.org/0000-0002-2663-2001, Balvočiūtė, Monika and Moulton, Vincent ORCID: https://orcid.org/0000-0001-9371-6435 (2018) SPECTRE: a Suite of PhylogEnetiC Tools for Reticulate Evolution. Bioinformatics, 34 (6). 1056–1057. ISSN 1367-4803

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Abstract

Split-networks are a generalization of phylogenetic trees that have proven to be a powerful tool in phylogenetics. Various ways have been developed for computing such networks, including split-decomposition, NeighborNet, QNet and FlatNJ. Some of these approaches are implemented in the user-friendly SplitsTree software package. However, to give the user the option to adjust and extend these approaches and to facilitate their integration into analysis pipelines, there is a need for robust, open-source implementations of associated data structures and algorithms. Here we present SPECTRE, a readily available, open-source library of data structures written in Java, that comes complete with new implementations of several pre-published algorithms and a basic interactive graphical interface for visualizing planar split networks. SPECTRE also supports the use of longer running algorithms by providing command line interfaces, which can be executed on servers or in High Performance Computing (HPC) environments.

Item Type:	Article
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Computational Biology > Phylogenetics (former - to 2018) Faculty of Science > Research Groups > Computational Biology Faculty of Science > Research Groups > Computational Biology > Computational biology of RNA (former - to 2018) Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre
Depositing User:	Pure Connector
Date Deposited:	22 Nov 2017 06:05
Last Modified:	14 Jun 2023 13:11
URI:	https://ueaeprints.uea.ac.uk/id/eprint/65525
DOI:	10.1093/bioinformatics/btx740

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