Advantages of this Tool
This tool has two advantages over traditional Enrichment tools
First and foremost it takes site information into account, which is an advantage because it increases the statistical confidence as the number of sites is greater than or equal to the number of proteins.
Furthermore, in this tool we use an FDR (false discovery rate) based approach to correct for the size of the dataset. Most approaches for corrections for multiple testing, such as Benjamini-Hochberg and Holm-Bonferroni, are not optimal for dataset that is correlated. For example, a protein that is annotated with the GO term "positive response to insulin signaling" will by definiton also be annotated with "response to insulin signaling". This tool therefore uses an FDR approach by drawing 500 random samples from the combined foreground and background datasets, and using the distributions of these "scrambled datasets" to estimate the FDR.