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. The input for each type of enrichment analysis is different. The Fisher's Exact Test requieres a list of IDs for the test-set sequences. On the other hand, the GSEA requires a ranked list of gene IDs where the first column is the sequence identifier and the second column (tab-separated) is the metric with biological meaning e.g 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 please continue reading here.
Enrichment Analysis options
References
- Rivals I, Personnaz L, Taing L, Potier MC. Enrichment or depletion of a GO category within a class of genes: which test? Bioinformatics. 2007;23(4):401-407. doi:10.1093/bioinformatics/btl633
- Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545-15550. doi:10.1073/pnas.0506580102