GO-Elite: a flexible solution for pathway and ontology over-representation
Open Access
- 27 June 2012
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 28 (16), 2209-2210
- https://doi.org/10.1093/bioinformatics/bts366
Abstract
Summary: We introduce GO-Elite, a flexible and powerful pathway analysis tool for a wide array of species, identifiers (IDs), pathways, ontologies and gene sets. In addition to the Gene Ontology (GO), GO-Elite allows the user to perform over-representation analysis on any structured ontology annotations, pathway database or biological IDs (e.g. gene, protein or metabolite). GO-Elite exploits the structured nature of biological ontologies to report a minimal set of non-overlapping terms. The results can be visualized on WikiPathways or as networks. Built-in support is provided for over 60 species and 50 ID systems, covering gene, disease and phenotype ontologies, multiple pathway databases, biomarkers, and transcription factor and microRNA targets. GO-Elite is available as a web interface, GenMAPP-CS plugin and as a cross-platform application. Availability:http://www.genmapp.org/go_elite Contact:nsalomonis@gladstone.ucsf.edu Supplementary Information: Supplementary data are available at Bioinformatics online.Keywords
This publication has 7 references indexed in Scilit:
- Consistency, comprehensiveness, and compatibility of pathway databasesBMC Bioinformatics, 2010
- Transcriptomic Profile Indicative of Immunotoxic Exposure: In Vitro Studies in Peripheral Blood Mononuclear CellsToxicological Sciences, 2010
- Opal web services for biomedical applicationsNucleic Acids Research, 2010
- The bovine lactation genome: insights into the evolution of mammalian milkGenome Biology, 2009
- Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene listsNucleic Acids Research, 2008
- A System-Based Approach to Interpret Dose- and Time-Dependent Microarray Data: Quantitative Integration of Gene Ontology Analysis for Risk AssessmentToxicological Sciences, 2006
- MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray dataGenome Biology, 2003