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Joaquin Dopazo, 05/30/2010 08:26 pm

Home >> Functional profiling documentation

FatiGO methods

Single enrichment analysis

The functional interpretation of genomic data is usually performed by studying the enrichment of any type of biologically relevant annotation in the genes or proteins selected by the experiment with respect to the corresponding distribution of the annotation in the background, typically the rest of genes or proteins in the genome.
Single enrichment analysis is less sensitive than gene set analysis and it is reccommended only in situations in which the genes are selected in the experiment in a categorical way (for example, because they are present in amplified or deleted regions or they are targets of regulatory factors, etc.)
In many cases this selection of genes is performed by multiple individual, gene-wise tests. This testing strategy is quite conservative and produces, at the end, a loss of testing power in the whole procedure because a large number of false negatives are sacrificed in order to preserve a low ratio of false positives.

FatiGO method

The FatiGO method (Al-Shahrour 2004) was the first proposal for functional enrichment that took into account the multiple testing problem. FatiGO works as follows:

  1. FatiGO takes two lists of genes. Ideally a group of interest and the rest of the genes in the experiment, although any two groups formed in any way, can be tested against each other.
  2. These two lists are converted into two lists of functional terms using the corresponding gene or protein - term annotation table.
  3. Then a Fisher's exact test for 2×2 contingency tables is used to check for significant over-representation of functional terms in one of the lists with respect to the other one.
  4. Multiple testing correction to account for the multiple hypothesis tested (one for each functional term) is applied. FatiGO uses the FDR B&H method.


  • Al-Shahrour, F., Minguez, P., Tárraga, J., Medina, I., Alloza, E., Montaner, D., & Dopazo, J. (2007). FatiGO+: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments. Nucleic Acids Research 35 (Web Server issue): W91-96
  • Al-Shahrour, F., Minguez, P., Tárraga, J., Montaner, D., Alloza, E., Vaquerizas, J.MM., Conde, L., Blaschke, C., Vera, J. & Dopazo, J. (2006). BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments. Nucleic Acids Research (Web Server issue) 34: W472-W476
  • Al-Shahrour, F., Minguez, P., Vaquerizas, J.M., Conde, L. & Dopazo, J. (2005). BABELOMICS: a suite of web-tools for functional annotation and analysis of group of genes in high-throughput experiments. Nucleic Acids Research, 33 (Web Server issue): W460-W464
  • Al-Shahrour, F., Díaz-Uriarte, R. & Dopazo, J. (2004). FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes. Bioinformatics 20: 578-580