Automatic functional profiling
A standard tool for automatic functional profiling accepts a query list of genes (referred to as set A, usually the set of genes experimentally identified to be related to the studied biological phenomena) and a reference set (referred to as set B, usually the set of all genes from the analyzed organism). Then, for each attribute f from the set F (f is usually a functional term from the employed annotation vocabulary F, i.e. GO, FunCat, etc.) the number af genes in set A and bf genes in set B that have been annotated with f is counted. In the next step the null hypothesis H0 (genes that belong to the set A are independent of having attribute f) is tested. Hypergeometric, binomial or Chi-Square tests are usually employed to find over/under represented attributes (Khatri, et al., 2004; Khatri, et al., 2005).