GOsummaries: an R Package for Visual Functional Annotation of Experimental Data

Area of Science:

• Computational Biology
• Bioinformatics
• Genomics

Background:

• Gene Ontology (GO) enrichment analysis is crucial for interpreting gene lists in computational biology.
• Interpreting numerous GO terms associated with single gene lists is challenging.
• Existing visualization tools are often limited to single gene list analysis.

Purpose of the Study:

• To introduce GOsummaries, a novel R package for visualizing and interpreting GO enrichment results.
• To provide a method for summarizing results from multiple gene lists.
• To enhance the interpretability of complex biological data analyses, including PCA.

Main Methods:

• Development of the 'GOsummaries' R package.
• Visualization of GO enrichment results using word clouds.
• Integration of raw experimental data graphs for comprehensive plots.
• Application to differential expression, clustering, and Principal Component Analysis (PCA).

Main Results:

• GOsummaries generates concise, combinable word clouds for multiple gene lists.
• The package facilitates rapid functional characterization of complex gene sets.
• GOsummaries significantly improves PCA interpretability by adding functional annotation.
• The approach is adaptable for non-gene data like metabolomics and metagenomics.

Conclusions:

• GOsummaries offers an effective solution for summarizing and interpreting complex GO enrichment results.
• The package enhances the functional characterization of various biological datasets, particularly PCA.
• GOsummaries improves the overall interpretability of high-throughput biological data analysis.