I'm performing some Gene Ontology enrichment analysis using R/Bioconductor and, as far as I understand, there are two packages that allow to do this: topGO and GOstats (I'm not interested in packages that compare multiple datasets in this scenario).
The main difference seems to be the statistics used: GOstats uses the hypergeometric distribution (basically the standard way to test for overrepresentation), while topGO allows the user to use a much wider and complete range of algorithms and statistical tests to check for enrichment.
With regards to graphic capabilities, topGO seems to be producing much better graphs than GOstats, but I have only looked at the packages' vignettes.
Has anybody here experience with both? Which one did you end up using? Why?
Also, on a related note, what would be the topGO algorithm/statistics test combination that emulates GOstats' hypergeometrical test? Would it be the classic/fisher combination (used as the most basic example in topGO's vignette)?