REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms

TLDR

High‑throughput experiments generate large, redundant Gene Ontology term lists that are difficult to interpret. REVIGO summarizes long Gene Ontology term lists by selecting a representative subset using a clustering algorithm based on semantic similarity. It visualizes the reduced set with multidimensional scaling, graph‑based layouts, treemaps, and tag clouds to reveal semantic relationships. REVIGO is freely available at http://revigo.irb.hr/.

Abstract

Outcomes of high-throughput biological experiments are typically interpreted by statistical testing for enriched gene functional categories defined by the Gene Ontology (GO). The resulting lists of GO terms may be large and highly redundant, and thus difficult to interpret. REVIGO is a Web server that summarizes long, unintelligible lists of GO terms by finding a representative subset of the terms using a simple clustering algorithm that relies on semantic similarity measures. Furthermore, REVIGO visualizes this non-redundant GO term set in multiple ways to assist in interpretation: multidimensional scaling and graph-based visualizations accurately render the subdivisions and the semantic relationships in the data, while treemaps and tag clouds are also offered as alternative views. REVIGO is freely available at http://revigo.irb.hr/.