ORA, FCS, and PT Strategies in Functional Enrichment Analysis

Downstream analysis of OMICS data requires interpretation of many molecular components considering current biological knowledge. Most tools used at present for functional enrichment analysis workflows applied to the field of proteomics are either borrowed or have been modified from genomics workflows to accommodate proteomics data. While the field of proteomics data analytics is evolving, as is the case for molecular annotation coverage, one can expect the rise of enhanced databases with less redundant ontologies spanning many elements of the tree of life. The methodology described here shows in practical steps how to perform overrepresentation analysis, functional class scoring, and pathway-topology analysis using a preexisting neurological dataset of proteomic data.