I was running DAVID v.6.8 Functional Annotation Tool on a gene list I entered. After running the program, I notice I get different values on Bonferroni correction after selecting different options on the “Annotation Summary Results.” For instance, If I select the “Check Defaults” box, I get different Bonferroni corrected p-values than when I select individual terms like GOTERM_BP_DIRECT, GOTERM_CC_DIRECT, GOTERM_MF_DIRECT, and KEGG Pathway.
Does the number of categories selected influence the results you obtain on the Functional Annotation Chart? Does this somehow influence Bonferroni or Benjamini calculations? I did not change any other settings other than those listed above.
Sorry I misread your question. I thought you are talking about the numbers in front of GOTERM_BP_#. But to answer your question, it shouldn't since I assume it runs the analysis separately over those datasets. However, make sure you are comparing apples to apples, meaning that you are comparing the p-values from the same pathway datasets to themselves not others.