PloGO: plotting gene ontology annotation and abundance in multi-condition proteomics experiments

Area of Science:

• Bioinformatics
• Proteomics
• Computational Biology

Background:

• Multi-condition label-free proteomics experiments generate complex datasets.
• Analyzing gene ontology (GO) annotations alongside protein abundance is crucial for biological interpretation.
• Existing tools may lack specific functionalities for integrating GO data with quantitative proteomics results.

Purpose of the Study:

• To introduce PloGO, an open-source R package designed for plotting GO annotation and abundance information.
• To facilitate the bioinformatics analysis of multi-condition label-free proteomics data.
• To aid in the identification of biologically relevant protein subsets and provide summarized GO information for further analysis.

Main Methods:

• The PloGO R package accepts raw spectral counts or normalized spectral abundance factors (NSAF) data.
• It integrates quantitative data with gene ontology (GO) annotations.
• The tool supports handling multiple experimental files and targeted selection of GO categories.

Main Results:

• PloGO enables visualization of GO annotation and abundance data from proteomics experiments.
• It assists in identifying protein subsets based on presence/absence or pairwise comparisons across conditions.
• The package provides easily usable GO summaries for subsequent bioinformatics analyses.

Conclusions:

• PloGO is a versatile, open-source tool for the analysis of multi-condition proteomics data.
• It enhances the interpretation of label-free quantitative proteomics experiments by integrating GO information.
• The package is applicable to any multi-condition experiment generating GO data, not limited to proteomics.