PyPathway: Python']Python Package for Biological Network Analysis and Visualization

被引:6
|
作者
Xu, Yang [1 ]
Luo, Xiao-Chun [1 ]
机构
[1] South China Univ Technol, Sch Biosci & Bioengn, Guangzhou Higher Educ Mega Ctr, Guangdong Prov Key Lab Fermentat & Enzyme Engn, Guangzhou 510006, Guangdong, Peoples R China
关键词
enrichment analysis; network analysis; pathway; visualization; PATHWAYS;
D O I
10.1089/cmb.2017.0199
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:499 / 504
页数:6
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