WebGIVI: a web-based gene enrichment analysis and visualization tool

BMC Bioinformatics

Software

Jia Ren¹  Carl J. Schmidt²  Liang Sun³  Jian Chen⁴  Yongnan Zhu⁵  K. Vijay-Shanker⁶  A. S. M. Ashique Mahmood⁶  Catalina O. Tudor⁶ 

[1] Center for Bioinformatics and Computational Biology, University of Delaware, 19711, Newark, DE, USA;Department of Animal and Food Sciences, University of Delaware, Newark, DE, USA;Department of Animal and Food Sciences, University of Delaware, Newark, DE, USA;Current address: Computing Service, The Samuel Roberts Noble Foundation, 73401, Ardmore, OK, USA;Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD, USA;Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD, USA;Department of Computer Science, Hangzhou Dianzi University, 310018, Hangzhou, Zhejiang Province, People’s Republic of China;Department of Computer and Information Sciences, University of Delaware, 19716, Newark, DE, USA;

关键词: Visualization;    eGIFT;    Gene iTerm;    Gene enrichment;    Web development;   

DOI  :  10.1186/s12859-017-1664-2

 received in 2017-03-06, accepted in 2017-04-28,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundA major challenge of high throughput transcriptome studies is presenting the data to researchers in an interpretable format. In many cases, the outputs of such studies are gene lists which are then examined for enriched biological concepts. One approach to help the researcher interpret large gene datasets is to associate genes and informative terms (iTerm) that are obtained from the biomedical literature using the eGIFT text-mining system. However, examining large lists of iTerm and gene pairs is a daunting task.ResultsWe have developed WebGIVI, an interactive web-based visualization tool (http://raven.anr.udel.edu/webgivi/) to explore gene:iTerm pairs. WebGIVI was built via Cytoscape and Data Driven Document JavaScript libraries and can be used to relate genes to iTerms and then visualize gene and iTerm pairs. WebGIVI can accept a gene list that is used to retrieve the gene symbols and corresponding iTerm list. This list can be submitted to visualize the gene iTerm pairs using two distinct methods: a Concept Map or a Cytoscape Network Map. In addition, WebGIVI also supports uploading and visualization of any two-column tab separated data.ConclusionsWebGIVI provides an interactive and integrated network graph of gene and iTerms that allows filtering, sorting, and grouping, which can aid biologists in developing hypothesis based on the input gene lists. In addition, WebGIVI can visualize hundreds of nodes and generate a high-resolution image that is important for most of research publications. The source code can be freely downloaded at https://github.com/sunliang3361/WebGIVI. The WebGIVI tutorial is available at http://raven.anr.udel.edu/webgivi/tutorial.php.

【 授权许可】

CC BY   
© The Author(s). 2017