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PyPathway:用于生物网络分析和可视化的Python软件包。

PyPathway: Python Package for Biological Network Analysis and Visualization.

作者信息

Xu Yang, Luo Xiao-Chun

机构信息

Guangdong Provincial Key Laboratory of Fermentation and Enzyme Engineering, School of Bioscience and Bioengineering, South China University of Technology , Guangzhou Higher Education Mega Center, Guangzhou, China .

出版信息

J Comput Biol. 2018 May;25(5):499-504. doi: 10.1089/cmb.2017.0199. Epub 2018 Apr 11.

Abstract

Life science studies represent one of the biggest generators of large data sets, mainly because of rapid sequencing technological advances. Biological networks including interactive networks and human curated pathways are essential to understand these high-throughput data sets. Biological network analysis offers a method to explore systematically not only the molecular complexity of a particular disease but also the molecular relationships among apparently distinct phenotypes. Currently, several packages for Python community have been developed, such as BioPython and Goatools. However, tools to perform comprehensive network analysis and visualization are still needed. Here, we have developed PyPathway, an extensible free and open source Python package for functional enrichment analysis, network modeling, and network visualization. The network process module supports various interaction network and pathway databases such as Reactome, WikiPathway, STRING, and BioGRID. The network analysis module implements overrepresentation analysis, gene set enrichment analysis, network-based enrichment, and de novo network modeling. Finally, the visualization and data publishing modules enable users to share their analysis by using an easy web application. For package availability, see the first Reference.

摘要

生命科学研究是大数据集的最大产生源之一,主要是由于测序技术的迅速发展。包括交互网络和人工整理的人类通路在内的生物网络对于理解这些高通量数据集至关重要。生物网络分析提供了一种方法,不仅可以系统地探索特定疾病的分子复杂性,还可以探索明显不同表型之间的分子关系。目前,已经为Python社区开发了几个软件包,如BioPython和Goatools。然而,仍然需要执行全面网络分析和可视化的工具。在这里,我们开发了PyPathway,这是一个可扩展的免费开源Python软件包,用于功能富集分析、网络建模和网络可视化。网络处理模块支持各种交互网络和通路数据库,如Reactome、WikiPathway、STRING和BioGRID。网络分析模块实现了超几何富集分析、基因集富集分析、基于网络的富集和从头网络建模。最后,可视化和数据发布模块使用户能够通过一个简单的Web应用程序共享他们的分析结果。有关软件包的可用性,请参阅第一个参考文献。

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