Bioinformatics · 2019 · 5.3K citations · 13 references
Life SciencesBioinformaticsMolecular BiologyComputational BiologyGenomicsPathway AnalysisFunctional Enrichment AnalysisGene Set Enrichment AnalysisGenomic DatabasesPathway AnnotationPathway DatabasesPathway VisualizationBiological Pathway DiagramsEnrichment AnalysisGene Ontology EnrichmentGene Set Annotation DatabasesGenome Annotation DatabasesLibrary Enrichment AnalysisNetwork-based Enrichment AnalysisPathway Diagram Annotation
Gene lists from omic studies are routinely generated, and enrichment analysis links them to molecular pathways and functional categories such as GO and other databases. The authors developed ShinyGO to complement existing tools by providing a large annotation database from Ensembl and STRING-db covering 59 plant, 256 animal, 115 archaeal, and 1678 bacterial species. ShinyGO incorporates graphical visualization of enrichment results and gene characteristics, and offers API access to KEGG and STRING for retrieving pathway diagrams and protein–protein interaction networks. ShinyGO is an intuitive, graphical web application that enables researchers to gain actionable insights from gene sets. ShinyGO is available at http://ge-lab.org/go/ and supplementary data are provided online.
Abstract Motivation Gene lists are routinely produced from various omic studies. Enrichment analysis can link these gene lists with underlying molecular pathways and functional categories such as gene ontology (GO) and other databases. Results To complement existing tools, we developed ShinyGO based on a large annotation database derived from Ensembl and STRING-db for 59 plant, 256 animal, 115 archeal and 1678 bacterial species. ShinyGO’s novel features include graphical visualization of enrichment results and gene characteristics, and application program interface access to KEGG and STRING for the retrieval of pathway diagrams and protein–protein interaction networks. ShinyGO is an intuitive, graphical web application that can help researchers gain actionable insights from gene-sets. Availability and implementation http://ge-lab.org/go/. Supplementary information Supplementary data are available at Bioinformatics online.
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