GSEA (Gene Set Enrichment Analysis) and Fisher's exact test are two different methods for analyzing gene expression data. While GSEA is a computational method that determines whether predefined sets of genes are enriched in a gene expression dataset, Fisher's exact test is a statistical method that assesses the association between two categorical variables, such as gene expression and a biological condition.
It is possible to use Fisher's exact test to assess the enrichment of a set of genes in a given biological condition. To perform this analysis, you would need to:
Define a set of genes of interest, such as those involved in a specific biological pathway or process.
Obtain a list of all genes that are expressed in the biological condition of interest.
Count the number of genes in the set of interest that are expressed in the biological condition.
Count the number of genes in the set of interest that are not expressed in the biological condition.
Count the number of genes not in the set of interest that are expressed in the biological condition.
Count the number of genes not in the set of interest that are not expressed in the biological condition.
Perform Fisher's exact test on a 2x2 contingency table with the counts from steps 3-6.
The output of Fisher's exact test will be a p-value, indicating the likelihood of observing the observed counts or more extreme counts, given that the null hypothesis (no association between gene expression and the set of interest) is true.
While Fisher's exact test can be a useful method for assessing the enrichment of a set of genes in a biological condition, GSEA is often preferred because it takes into account the entire distribution of gene expression in the dataset and can identify subtle but coordinated changes in gene expression that may be missed by simpler methods.
