PhyKIT: a broadly applicable UNIX shell toolkit for processing and analyzing phylogenomic data

• Published in: Bioinformatics (Oxford, England) Vol. 37; no. 16; pp. 2325 - 2331
• Main Authors: Steenwyk, Jacob L, Buida, Thomas J, Labella, Abigail L, Li, Yuanning, Shen, Xing-Xing, Rokas, Antonis
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 25-08-2021; Oxford Publishing Limited (England)
• Subjects: Availability; Bias; Bioinformatics; Biological evolution; Information processing; Mutation rates; Original Papers; Phylogenetics; Phylogeny; Toolkits; UNIX
• ISSN: 1367-4803; 1367-4811
• DOI: 10.1093/bioinformatics/btab096

Abstract
Motivation
Diverse disciplines in biology process and analyze multiple sequence alignments (MSAs) and phylogenetic trees to evaluate their information content, infer evolutionary events and processes and predict gene function. However, automated processing of MSAs and trees remains a challenge due to the lack of a unified toolkit. To fill this gap, we introduce PhyKIT, a toolkit for the UNIX shell environment with 30 functions that process MSAs and trees, including but not limited to estimation of mutation rate, evaluation of sequence composition biases, calculation of the degree of violation of a molecular clock and collapsing bipartitions (internal branches) with low support.
Results
To demonstrate the utility of PhyKIT, we detail three use cases: (1) summarizing information content in MSAs and phylogenetic trees for diagnosing potential biases in sequence or tree data; (2) evaluating gene–gene covariation of evolutionary rates to identify functional relationships, including novel ones, among genes and (3) identify lack of resolution events or polytomies in phylogenetic trees, which are suggestive of rapid radiation events or lack of data. We anticipate PhyKIT will be useful for processing, examining and deriving biological meaning from increasingly large phylogenomic datasets.
Availability and implementation
PhyKIT is freely available on GitHub (https://github.com/JLSteenwyk/PhyKIT), PyPi (https://pypi.org/project/phykit/) and the Anaconda Cloud (https://anaconda.org/JLSteenwyk/phykit) under the MIT license with extensive documentation and user tutorials (https://jlsteenwyk.com/PhyKIT).
Supplementary information
Supplementary data are available at Bioinformatics online.