Department of Biology, University of Waterloo, Waterloo, Canada.
Bioinformatics. 2019 Dec 1;35(23):5063-5065. doi: 10.1093/bioinformatics/btz522.
A critical step in comparative genomics is the identification of differences in the presence/absence of encoded biochemical pathways among organisms. Our library, Pygenprop, facilitates these comparisons using data from the Genome Properties database. Pygenprop is written in Python and, unlike existing libraries, it is compatible with a variety of tools in the Python data science ecosystem, such as Jupyter Notebooks for interactive analyses and scikit-learn for machine learning. Pygenprop assigns YES, NO, or PARTIAL support for each property based on InterProScan annotations of open reading frames from an organism's genome. The library contains classes for representing the Genome Properties database as a whole and methods for detecting differences in property assignments between organisms. As the Genome Properties database grows, we anticipate widespread adoption of Pygenprop for routine genome analyses and integration within third-party bioinformatics software.
Pygenprop is written in Python and is compatible with versions 3.6 or higher. Source code is available under Apache Licence Version 2 at https://github.com/Micromeda/pygenprop. The package can be installed from both PyPi (https://pypi.org/project/pygenprop) and Anaconda (https://anaconda.org/lbergstrand/pygenprop). Documentation is available on Read the Docs (http://pygenprop.rtfd.io/).
比较基因组学的一个关键步骤是识别生物体之间编码生化途径存在/缺失的差异。我们的 Pygenprop 库使用来自基因组属性数据库的数据来促进这些比较。Pygenprop 是用 Python 编写的，与现有的库不同，它与 Python 数据科学生态系统中的各种工具兼容，如用于交互式分析的 Jupyter Notebooks 和用于机器学习的 scikit-learn。Pygenprop 根据生物体基因组中开放阅读框的 InterProScan 注释，为每个属性分配 YES、NO 或 PARTIAL 支持。该库包含表示整个基因组属性数据库的类，以及用于检测生物体之间属性分配差异的方法。随着基因组属性数据库的增长，我们预计 Pygenprop 将被广泛用于常规基因组分析，并集成到第三方生物信息学软件中。
Pygenprop 是用 Python 编写的，与 3.6 或更高版本兼容。源代码可在 Apache 许可证版本 2 下在 https://github.com/Micromeda/pygenprop 获得。该包可从 PyPi（https://pypi.org/project/pygenprop）和 Anaconda（https://anaconda.org/lbergstrand/pygenprop）安装。文档可在 Read the Docs（http://pygenprop.rtfd.io/）上获得。
