Abstract
We introduce Pyvolve, a flexible Python module for simulating genetic data along a phylogeny using continuous-time Markov models of sequence evolution. Easily incorporated into Python bioinformatics pipelines, Pyvolve can simulate sequences according to most standard models of nucleotide, amino-acid, and codon sequence evolution. All model parameters are fully customizable. Users can additionally specify custom evolutionary models, with custom rate matrices and/or states to evolve. This flexibility makes Pyvolve a convenient framework not only for simulating sequences under a wide variety of conditions, but also for developing and testing new evolutionary models. Pyvolve is an open-source project under a FreeBSD license, and it is available for download, along with a detailed user-manual and example scripts, from http://github.com/sjspielman/pyvolve.
Highlights
The Python programming language has become a staple in biological computing
In computational molecular evolution and phylogenetics, sequence simulation represents a fundamental aspect of model development and testing
Because Pyvolve focuses on simulating the substitution processes using continuous-time Markov models along a fixed phylogeny, it is most suitable for simulating gene sequences, benchmarking inference frameworks, and for developing and testing novel Markov models of sequence evolution
Summary
The Python programming language has become a staple in biological computing. In particular, the molecular evolution community has widely embraced Python as standard tool, in part due to the development of powerful bioinformatics modules such as Biopython [1] and DendroPy [2]. Pyvolve simulates sequences along a phylogeny using continuous-time Markov models of sequence evolution for nucleotides, amino acids, and codons, according to standard approaches [5]. Pyvolve allows users to specify and evolve custom evolutionary models and/or states, making Pyvolve an ideal engine for novel model development and testing.
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