Abstract
Functional enrichment analysis is an essential task for the interpretation of gene lists derived from large-scale genetic, transcriptomic and proteomic studies. WebGestalt (WEB-based GEne SeT AnaLysis Toolkit) has become one of the popular software tools in this field since its publication in 2005. For the last 7 years, WebGestalt data holdings have grown substantially to satisfy the requirements of users from different research areas. The current version of WebGestalt supports 8 organisms and 201 gene identifiers from various databases and different technology platforms, making it directly available to the fast growing omics community. Meanwhile, by integrating functional categories derived from centrally and publicly curated databases as well as computational analyses, WebGestalt has significantly increased the coverage of functional categories in various biological contexts including Gene Ontology, pathway, network module, gene–phenotype association, gene–disease association, gene–drug association and chromosomal location, leading to a total of 78 612 functional categories. Finally, new interactive features, such as pathway map, hierarchical network visualization and phenotype ontology visualization have been added to WebGestalt to help users better understand the enrichment results. WebGestalt can be freely accessed through http://www.webgestalt.org or http://bioinfo.vanderbilt.edu/webgestalt/.
Highlights
High-throughput genomic, transcriptomic and proteomics technologies have transformed biological research by enabling comprehensive investigations of biological systems
In response to this critical need, in the 2005 NAR (Nucleic Acids Research) Web Server Issue, we presented WebGestalt (WEB-based GEne SeT AnaLysis Toolkit) [1], one of the first software applications that integrate functional enrichment analysis and information visualization for the management, information retrieval, organization, visualization and statistical analysis of large sets of genes
The tool has been widely used in large-scale genetic, transcriptomic and proteomic studies, with more than 400 citations reported by Google Scholar as of the time of writing
Summary
High-throughput genomic, transcriptomic and proteomics technologies have transformed biological research by enabling comprehensive investigations of biological systems. The old version of WebGestalt only supported seven gene identifiers from a few public databases for human and mouse, including Entrez Gene ID, Nucleic Acids Research, 2013, Vol 41, Web Server issue W79 The new version of WebGestalt supports identifiers from more public databases and recognizes identifiers from major high-throughput platforms for human and seven important model organisms including mouse, rat, worm, fly, yeast, dog and zebrafish.
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