Authors:
Aleksandr Koshkarov
and
Nadia Tahiri
Affiliation:
Département d’Informatique, Université de Sherbrooke, 2500 Boulevard de l’Université, Sherbrooke, Québec J1K 2R1, Canada
Keyword(s):
Bioinformatics, Phylogenetics, Simulation, Tree Generator, Supertrees.
Abstract:
Summary: More and more evolutionary and molecular biologists are interested in building alternative supertrees. Often, developing new approaches or testing new metrics requires relevant datasets that are not always easy to obtain. In order to solve this problem of lack of data, we propose a new approach and developed a program in Python to generate overlapping phylogenetic trees with biological events to simplify the process of obtaining this type of data. The new tool takes the number of phylogenetic trees the user wants to generate, the maximum number of leaves per tree to generate, and the average level of leaf overlap between phylogenetic trees as input parameters. The program returns to the user a set of phylogenetic trees in Newick format, respecting the parameters given as input, in order to use them to infer a supertree (or supertrees). This data can be an important resource for research; the user can download the generated data and use it later in their relevant application
tasks. Availability and implementation: The generator is freely and publicly available to the entire scientific community on the GitHub platform, without any registration, https://github.com/tahiri-lab/gptree under the MIT licence. The pipeline is written in Python 3.7.
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