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

Hugo P Bastos1, Lisete Sousa2, Luka A Clarke3

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Summary

Annotation heterogeneity in biological sequences complicates functional similarity assessment. GRYFUN, a web application, visualizes Gene Ontology (GO) annotations and statistics for protein sets, aiding interpretation and analysis of functional coherence.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Biological sequence annotations provide functional context but can exhibit heterogeneity in coverage and specificity within related sequence groups.
  • This annotation heterogeneity poses challenges for accurately interpreting functional similarity and the overall functional coherence of sequence sets.

Purpose of the Study:

  • To address the interpretation issues arising from annotation heterogeneity.
  • To develop a tool for visualizing and statistically assessing Gene Ontology (GO) annotations in protein sets.

Main Methods:

  • Creation of a web application, GRYFUN, accessible at http://xldb.di.fc.ul.pt/gryfun/.
  • The application accepts UniProt accession numbers to define protein sets.
  • GRYFUN generates Gene Ontology annotation graphs and calculates associated statistics, including frequencies, enrichment values, and Information Content metrics.

Main Results:

  • GRYFUN provides a user-friendly interface for visualizing GO annotations of user-defined protein sets.
  • The tool offers statistical assessments to quantify annotation coherence and cohesiveness.
  • It facilitates the analysis of annotation extension for under-annotated protein sets.

Conclusions:

  • GRYFUN effectively mitigates issues related to annotation heterogeneity by providing visualization and statistical analysis.
  • The web application aids in assessing functional similarity and coherence within protein sets.
  • GRYFUN is a valuable resource for researchers studying protein function and annotation quality.