Enrichment analysis is usually to analyze whether a group of genes are overexpressed at a functional node. This principle can be developed from annotation analysis of a single gene to grouping analysis of a large genome.
Because the conclusion of analysis is based on a group of related genes, rather than a single gene, enrichment analysis method increases the reliability of research and can also identify the biological processes most related to biological phenomena.
Commonly used websites with rich functions are agrigo and David.
Here, DAVID, which is widely used at present, is taken as an example to analyze the gene set in detail. DAVID is a comprehensive tool, which not only provides gene enrichment analysis, but also provides ID conversion between genes and classification of gene functions.
Functional prediction of 1. differentially expressed genes.
In the data analysis of gene chip, researchers can find out which differentially expressed genes belong to the same branch of GO function, and use statistical methods to test whether the results are statistically significant, so as to find out which biological functions the differentially expressed genes mainly participate in.
Path analysis is a commonly used gene function analysis method for chip data. Different from GO classification (using the GO classification information of a single gene), the resources used in pathway analysis are the interactions between many genes that have been clearly studied, that is, biological pathways. Researchers can import the set of genes with changed expression into the pathway analysis software, and then find out which known pathways the changed genes exist in, and calculate which pathways are most related to the change of gene expression through statistical methods.