Pathway analysis of omics data: Overrepresentation Analysis

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High-throughput technologies (e.g., genomics, transcriptomics, proteomics) are widely used to monitor the activity of thousands of genes in a single experiment. These result in hundreds or thousands of differentially expressed genes leaving the researcher with the challenging task of understanding their biological relevance. Due to its simplicity, well-established statistical model, and ease of implementation, enrichment through Overrepresentation Analysis (ORA) is commonly used to interpret lists of differentially expressed genes and it is also available through many online tools. However, this method may result in dozens of pathways, and gene ontology functions. Attendees to this session will learn:

• what are the components of an ORA: gene list, cutoffs, background, or reference set, etc.
• how to use gProfiler, an online tool for enrichment analysis
• how to visualize and present the results of the enrichment analysis.

Requisites

Download and install Cytocape