GO Analysis

Gene Ontology (GO) Enrichment Analyses are widely used to analyze omics-data sets to identify significant enriched GO terms. AlphaStats utilizes aGOtool for enrichment analysis. aGOtool is specially tailored for Mass Spectrometry (MS) based proteomics data. This tool considers the fact that post-translational modifications (PTMs) are more likely to be detected on highly abundant proteins than on low-abundant proteins. The functional enrichment is performed for GO (molecular function, biological process, cellular component), UniProt keywords, KEGG pathways, PubMed publications, Reactome, Wiki Pathways, Interpro domains, PFAM domains, Brenda Tissues and Diseases. The bias correction by aGOtool aims for increased specificity, fewer significantly enriched but more biologically meaningful and accurate enrichment terms Schölz et al. 2015.

The implementation of aGOtool in AlphaStats will allow you to perform the following analysis:

  • Abundance Correction: Compares two samples (for example healthy vs. controls). As foreground, all positively, associated proteins of the foreground are used. For the background postively associated proteins and their intensity of the background are used.

  • Characterize Foreground: Display functional annotations of your Protein(s) of interest without performing a statistical test.

  • Compare Samples: GO Enrichment ANalysis without abundance correction.

  • Genome: GO Enrichment Analysis using a Background from UniProt Reference Proteomes.

All functions will return a pandas DataFrame with the results.

Requirements

A GO Enrichment Analysis using Proteomics data is usually performed on a list of proteins with specific PTMs. Currently, AlphaStats offers the option to load the evidence.txt file from MaxQuant. This file will be used to extract proteins with PTMs when performing a GO analysis. In case there is no information about PTMs available, a list of upregulated proteins in form of UniProt protein accession numbers can be passed to the functions.

More details about the GO Analysis can be found here: