---
title: Functional Enrichment
slug: functional-enrichment
createdAt: 2026-04-27T07:51:56.001Z
---

For knowledge-based insights into biological processes and disease associations over‑represented in the generated graph (or a selection of graph nodes) you can use functional enrichment. Use the Included Genes drop-down menu to choose whether the analysis runs on all genes in the graph or only on your selected genes. You can perform Gene Ontology ([1](docId:-p-TocFcINjHyxTCb7Fnb)) biological process, molecular function or cellular component enrichment analysis, as well as disease associated genes (Resource: ClinGen ([2](docId:-p-TocFcINjHyxTCb7Fnb))), Rare Disease associated genes (Resource: Orphadata ([3](docId:-p-TocFcINjHyxTCb7Fnb))), or [Mavatar curated list of genes](docId:-vnEz3H3bxwdbsZ9436Xy). This test will tell whether genes within any of these category-functions appear more often than expected by chance among the selected genes. This can support you to gain knowledge-based insights into biological context of your gene lists.

The enrichment P-Value is calculated using the Hypergeometric distribution function adjusting for multiple testing with Benjamini-Hochberg (BH) to decrease the false discovery rate (FDR). The gene background is defined as the intersection of the genes included in the network and in the GO database. To account for the Directed Acylic Graph (DAG) nature of GO-terms, an “elim”-approach is implemented, as previously described by Alexa et al., Bioinformatics, 2006 ([4](docId:-p-TocFcINjHyxTCb7Fnb)). As a result, genes annotated to a child term are also included under its parent terms. 

Enrichment results are presented in a figure where top 30 enriched terms are presented in rows. The gene ratio (overlap between selected genes and the term) is presented by the size of the dot, the significance is represented by the color (the deeper orange color the lower the adjusted for multiple testing P-value).  Hover with your cursor over the term name to get detailed information about the term itself, its size, overlap, gene ratio and adjusted P-value. Click on the orange count number to see which genes overlap between the generated graph and the term. Hovering over the dot will provide you with exact number of gene ratio.

:::hint{type="info"}
By right-clicking on the term name, you can select [Add](docId\:fnr1Vl5zxsmM8JOMxdyc5) and generate a new graph including all genes within that term or gene list. 
:::

# References

1. The Gene Ontology Consortium, The Gene Ontology knowledgebase in 2023. Genetics 224 (2023), doi:10.1093/GENETICS/IYAD031. ([https://geneontology.org/](https://geneontology.org/))
2. Welcome to ClinGen (available at [https://www.clinicalgenome.org/](https://www.clinicalgenome.org/)).
3. Orphadata – Orphanet datasets (available at [https://www.orphadata.com/](https://www.orphadata.com/)).
4. A. Alexa, J. Rahnenführer, T. Lengauer, Improved scoring of functional groups from gene expression data by decorrelating GO graph structure. Bioinformatics 22, 1600–1607 (2006). ([https://doi.org/10.1093/bioinformatics/btl140](https://doi.org/10.1093/bioinformatics/btl140))