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 environments.
Full source code is available under the GPLv3 license at: https://github.com/maplesond/SPECTRE. SPECTRE’s core library is available from Maven Central at: https://mvnrepository.com/artifact/uk.ac.uea.cmp.spectre/core. Documentation is available at: http://spectre-suite-of-phylogenetic-tools-for-reticulate-evolution.readthedocs.io/en/latest/
Supplementary data are available at Bioinformatics online.
1 Introduction
Split-networks are a generalization of phylogenetic trees that are commonly used to analyze reticulate evolution in organisms such as plants, bacteria and viruses (see Fig. 1 for an example). They provide a snapshot of the data and can be used to display conflicting signals. Examples of algorithms for computing such networks include split-decomposition (Bandelt and Dress, 1992), Neighbor-Net (Bryant and Moulton, 2004), QNet (Grünewald et al., 2007), SuperQ (Grünewald et al., 2013) and FlatNJ (Balvočiūtė et al., 2014). A comprehensive overview of split-networks can be found in (Huson and Bryant, 2006). Currently, the main program available for computing split-networks is the user-friendly SplitsTree program (Huson and Bryant, 2006). In addition, various methods for computing split-networks such as some of those mentioned above have been implemented and released as stand alone applications. Implementing data structures capable of representing the mathematical structures used to describe and compute split networks is not a trivial undertaking and existing software either is closed source or have their data structures and algorithms tightly integrated with their host tool, so are not easily reusable. There are, therefore, currently few options for developers wishing to create or extend their own tools based on these concepts other than to start from scratch. Hence, there is a need for a robust and flexible open-source library that provides core data structures and algorithms to facilitate development of new tools.
To illustrate some of SPECTREs functionality, we processed a dataset analyzed in (Bollyky et al., 1996) consisting of different Hepatitis B viruses (HBV). There are five different genomic groups and the phylogenetic analysis led to the result that HBVDNA is a recombinant with around half the genome coming from group A and half from group D. It also concluded that HPBADW1 is a recombinant of HPBADW2 (B) and HPBADWZCG (A), but with only a small insertion from HPBADWZCG into the Genome. (a) A minimum evolution tree constructed by NetME that is compatible with the split network constructed by NeighborNet, which is shown in (b). (c) The split network constructed by FlatNJ
2 SPECTRE
Here, we present SPECTRE, a suite of tools for computing, modelling and visualizing reticulate evolution based on split-networks. SPECTRE builds in part on existing open-source implementations of some of these tools, in particular for QNet, SuperQ and FlatNJ, integrating them into a unified and extendible library. The main tools available through SPECTRE are summarized below (for more details see Section 1 of Supplementary Material):
NeighborNet rapidly constructs a circular split network from a distance matrix or a sequence alignment (Bryant and Moulton, 2004). NetMake implements variants of NeighborNet as described in (Levy and Pachter, 2011).
SuperQ constructs a circular split network from a set of (partial) input trees (Grünewald et al., 2013).
FlatNJ constructs a flat split network from a multiple sequence alignment, weighted quartet data or location data (Balvočiūtė et al., 2014).
NetME produces a minimum evolution tree compatible with an existing circular split network (Bastkowski et al., 2014).
3 Concluding remarks
SPECTRE provides a collection of open-source tools and resources for modelling, understanding and visualizing reticulate evolution based on split networks. We believe that our software will both enable bioinformaticians to easily test and compare methods for inferring planar split networks and help computer scientists build their own methods for inferring phylogenetic networks by reusing our existing data structures and algorithms via the open-source library. Moreover, this also provides the option to easily add such new tools to the library making them readily available to other users.
Acknowledgement
The authors would like to thank Stephan Grünewald.
Conflict of Interest: none declared.
References
Author notes
The authors wish it to be known that, in their opinion, Sarah Bastkowski and Daniel Mapleson authors should be regarded as Joint First Authors.
