A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool

Bioinformatics. 2016 Feb 1;32(3):477-9. doi: 10.1093/bioinformatics/btv590. Epub 2015 Oct 17.

Abstract

Summary: Gene Ontology (GO) semantic similarity measures are being used for biological knowledge discovery based on GO annotations by integrating biological information contained in the GO structure into data analyses. To empower users to quickly compute, manipulate and explore these measures, we introduce A-DaGO-Fun (ADaptable Gene Ontology semantic similarity-based Functional analysis). It is a portable software package integrating all known GO information content-based semantic similarity measures and relevant biological applications associated with these measures. A-DaGO-Fun has the advantage not only of handling datasets from the current high-throughput genome-wide applications, but also allowing users to choose the most relevant semantic similarity approach for their biological applications and to adapt a given module to their needs.

Availability and implementation: A-DaGO-Fun is freely available to the research community at http://web.cbio.uct.ac.za/ITGOM/adagofun. It is implemented in Linux using Python under free software (GNU General Public Licence).

Contact: gmazandu@cbio.uct.ac.za or Nicola.Mulder@uct.ac.za

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods*
  • Databases, Factual
  • Gene Ontology*
  • Genes*
  • Humans
  • Molecular Sequence Annotation / methods*
  • Proteins / genetics*
  • Semantics*
  • Software*

Substances

  • Proteins