Your gene universe should really be limited to the original set from which your significant genes were taken.  For example, if your 28 significant genes were derived from an analysis of whole human genome microarrays, then you would limit your gene universe to just the ensembl gene IDs for the human genome (which is something like 20,300 or thereabouts).

Gene ontology hypergeometric enrichment is derived from basic set theory.  It is just the probability of k successes in n draws without replacement from a finite population of size N containing exactly K successes.  If you arbitrarily over-define one of the sets for comparison (K or N), you bias your enrichment results.

P.S. as an example of how to code TopGO to restrict your enrichment, here is an example from the Baliga lab at the Inst. for Systems Biology - http://baliga.systemsbiology.net/events/sysbio/sites/baliga.systemsbiology.net.events.sysbio/files/uploads/topGO_FunctionalEnrichment.r

The example looks for enrichment of a very small subset of human genes associated with glioblastoma (a type of brain tumors).

Your gene universe should really be limited to the original set from which your significant genes were taken.  For example, if your 28 significant genes were derived from an analysis of whole human genome microarrays, then you would limit your gene universe to just the ensembl gene IDs for the human genome (which is something like 20,300 or thereabouts).

Gene ontology hypergeometric enrichment is derived from basic set theory.  It is just the probability of k successes in n draws without replacement from a finite population of size N containing exactly K successes.  If you arbitrarily over-define one of the sets for comparison (K or N), you bias your enrichment results.

P.S. as an example of how to code TopGO to restrict your enrichment, here is an example from the Baliga lab at the Inst. for Systems Biology - http://baliga.systemsbiology.net/events/sysbio/sites/baliga.systemsbiology.net.events.sysbio/files/uploads/topGO_FunctionalEnrichment.r

The example looks for enrichment of a very small subset of human genes associated with glioblastoma (a type of brain tumors).

Easy alternative is Amigo GO db.

Hi,

You can use term enrichment tool available to the GO website/AmiGO for your analysis-

http://geneontology.org/

http://amigo.geneontology.org

FYI-The term enrichment tool available at both these URLs are the same.

Best,

Rama

Hi,

you can find the detailed explanation of the example provided by  Dr Micheal B Black in the "Gene set enrichment analysis with topGO" pdf guide on Bioconductor web site "http://www.bioconductor.org/packages/release/bioc/vignettes/topGO/inst/doc/topGO.pdf", at paragraph 4.4 "Predefined list of interesting genes".

I didn't know this package until now. Thank you.

Regards,

Giulia

Hi 

I have RNA sequencing data for 4 different samples. Can you please explain how to do the data analysis? to find out the deferentially expressed gene and its function