Spielman Stephanie J, Wilke Claus O
Department of Integrative Biology, Center for Computational Biology and Bioinformatics, and Institute of Cellular and Molecular Biology, The University of Texas at Austin, Austin, TX 78712, United States of America.
PLoS One. 2015 Sep 23;10(9):e0139047. doi: 10.1371/journal.pone.0139047. eCollection 2015.
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.
我们介绍Pyvolve,这是一个灵活的Python模块,用于使用序列进化的连续时间马尔可夫模型沿着系统发育树模拟遗传数据。Pyvolve可以轻松地集成到Python生物信息学管道中,根据大多数核苷酸、氨基酸和密码子序列进化的标准模型来模拟序列。所有模型参数均可完全定制。用户还可以指定自定义进化模型,包括自定义速率矩阵和/或要进化的状态。这种灵活性使Pyvolve不仅成为在各种条件下模拟序列的便捷框架,还成为开发和测试新进化模型的便捷框架。Pyvolve是一个遵循FreeBSD许可的开源项目,可从http://github.com/sjspielman/pyvolve下载,同时还提供详细的用户手册和示例脚本。