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Enrichment Analysis

Introduction

A functional enrichment analysis is the procedure of identifying functions that are over- or under-represented among a set of genes and may have an association with an experimental condition like for example phenotype or drug treatment. To obtain functional profiles for list of genes helps to gain a better understanding of the underlying biological processes. Enrichment analysis methods use statistical approaches to identify significantly enriched or depleted functions among a group of genes.

There are two main types of enrichment analysis:

  • Over Representation Analysis: This method compares the functional annotations of two lists of genes against each other. It tests for each function, e.g. a GO term, if it is more frequent in one list compared to another list i.e. a reference set or background. This type of enrichment is calculated via a contingency table used in statistical tests like e.g. a Fisher’s Exact Test.
  • Gene Set Enrichment Analysis (GSEA): This method tests if genes of a gene set (i.e. a group of genes annotated with the same GO term) accumulate in the upper or lower part of a ranked list of genes. A gene list can be ranked by any metric with biological meaning e.g. expression values or methylation level, etc.

The Functional Analysis module in OmicsBox allows performing both types of tests, each documented on its own page:

  • Fisher's Exact Test for over-representation analysis. It requires a list of IDs for the test-set sequences.
  • Gene Set Enrichment Analysis for the ranked-list approach. It requires a ranked list of gene IDs where the first column is the sequence identifier and the second column (tab-separated) is a metric with biological meaning, for example the logFC.

Both types of lists can be generated from within OmicsBox or imported as a plain text file. For a detailed tutorial on how to prepare these lists, see this tutorial.

Figure 1. Enrichment Analysis options in the Side Panel.

References