GRYFUN: a web application for GO term annotation visualization and analysis in protein sets

PLoS One. 2015 Mar 20;10(3):e0119631. doi: 10.1371/journal.pone.0119631. eCollection 2015.

Abstract

Functional context for biological sequence is provided in the form of annotations. However, within a group of similar sequences there can be annotation heterogeneity in terms of coverage and specificity. This in turn can introduce issues regarding the interpretation of actual functional similarity and overall functional coherence of such a group. One way to mitigate such issues is through the use of visualization and statistical techniques. Therefore, in order to help interpret this annotation heterogeneity we created a web application that generates Gene Ontology annotation graphs for protein sets and their associated statistics from simple frequencies to enrichment values and Information Content based metrics. The publicly accessible website http://xldb.di.fc.ul.pt/gryfun/ currently accepts lists of UniProt accession numbers in order to create user-defined protein sets for subsequent annotation visualization and statistical assessment. GRYFUN is a freely available web application that allows GO annotation visualization of protein sets and which can be used for annotation coherence and cohesiveness analysis and annotation extension assessments within under-annotated protein sets.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods*
  • Databases, Protein*
  • Datasets as Topic
  • Gene Ontology*
  • Molecular Sequence Annotation / methods*
  • Software*
  • Web Browser*

Grants and funding

This work was supported by the Portuguese Fundacao para a Ciencia e Tecnologia through the PhD Grant ref. SFRH/BD/48035/2008 to HPB and projects PTDC/MAT/118335/2010, PEst-OE/MAT/UI0006/2014 to LS, PEst-OE/BIA/UI4046/2011 (BioFIG) to LAC, and PEst-OE/EEI/UI0408/2014 (LaSIGE) to HPB and FMC, and by the European Commission (http://ec.europa.eu <http://ec.europa.eu>) through the BiobankCloud project under the Seventh Framework Programme (grant #317871) to FMC. Additionally we like to thank FCUL for the tuition support for HPB. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.