WebGIVI: a web-based gene enrichment analysis and visualization tool
Author(s) | Sun, Liang | |
Author(s) | Zhu, Yongnan | |
Author(s) | Mahmood, A. S. M. Ashique | |
Author(s) | Tudor, Catalina O. | |
Author(s) | Ren, Jia | |
Author(s) | Vijay-Shanker, K. | |
Author(s) | Chen, Jian | |
Author(s) | Schmidt, Carl J. | |
Ordered Author | Liang Sun, Yongnan Zhu, A. S. M. Ashique Mahmood, Catalina O. Tudor, Jia Ren, K. Vijay-Shanker, Jian Chen and Carl J. Schmidt | |
UD Author | Sun, Liang | en_US |
UD Author | Mahmood, A. S. M. Ashique | en_US |
UD Author | Tudor, Catalina O. | en_US |
UD Author | Ren, Jia | en_US |
UD Author | Vijay-Shanker, K. | en_US |
UD Author | Schmidt, Carl J. | en_US |
Date Accessioned | 2017-09-12T16:50:47Z | |
Date Available | 2017-09-12T16:50:47Z | |
Copyright Date | Copyright © The Author(s). 2017 | en_US |
Publication Date | 2017-05-04 | |
Description | Publisher's PDF | en_US |
Abstract | BACKGROUND: A 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. RESULTS: We 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. CONCLUSIONS: WebGIVI 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. | en_US |
Department | University of Delaware. Department of Animal and Food Sciences. | en_US |
Department | University of Delaware. Department of Computer and Information Sciences. | en_US |
Department | University of Delaware. Center for Bioinformatics & Computational Biology. | en_US |
Citation | Sun et al. BMC Bioinformatics (2017) 18:237 DOI 10.1186/s12859-017-1664-2 | en_US |
DOI | 10.1186/s12859-017-1664-2 | en_US |
ISSN | 1471-2105 | en_US |
URL | http://udspace.udel.edu/handle/19716/21642 | |
Language | en_US | en_US |
Publisher | BioMed Central | en_US |
dc.rights | Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. | en_US |
dc.source | BMC Genomics | en_US |
dc.source.uri | https://bmcbioinformatics.biomedcentral.com/ | en_US |
Title | WebGIVI: a web-based gene enrichment analysis and visualization tool | en_US |
Type | Article | en_US |