GOrilla - a tool for identifying enriched GO terms

GORILLA

Gene Ontology enRIchment anaLysis and visuaLizAtion tool

GOrilla is a tool for identifying and visualizing enriched GO terms in ranked lists of genes.
It can be run in one of two modes:

Searching for enriched GO terms that appear densely at the top of a ranked list of genes or
Searching for enriched GO terms in a target list of genes compared to a background list of genes.

For further details see References.

Running example Usage instructions GOrilla News(Updated March 8th 2013) References

Step 1: Choose organism

Step 2: Choose running mode

Single ranked list of genes       Two unranked lists of genes (target and background lists)

Step 3: Paste a ranked list of gene/protein names
Names should be separated by an <ENTER>. The preferred format is gene symbol. Other supported formats are: gene and protein RefSeq, Uniprot, Unigene and Ensembl. Use WebGestalt for conversion from other identifier formats.

Target set:

Or upload a file:

Background set:

Or upload a file:

Step 4: Choose an ontology

Process       Function      Component    All

Advanced parameters

P-value threshold:

Analysis name: (optional)

E-mail address: (optional - enter an e-mail address if you would like to receive a link to your results)

Output results in Microsoft Excel format

Include unresolved and duplicate genes in output

Show output also in REViGO

Run GOrilla in fast mode

References

If you choose to use this application please cite:

Eran Eden*, Roy Navon*, Israel Steinfeld, Doron Lipson and Zohar Yakhini. "GOrilla: A Tool For Discovery And Visualization of Enriched GO Terms in Ranked Gene Lists", BMC Bioinformatics 2009, 10:48.
Eran Eden, Doron Lipson, Sivan Yogev, Zohar Yakhini. "Discovering Motifs in Ranked Lists of DNA sequences", PLoS Computational Biology, 3(3):e39, 2007.

Graphics are generated using Graphviz.

Components of the GOrilla system were designed as part of the European Union FP6 funded Multi Knowledge Project.

http://www.multiknowledge.org/

Creating New Knowledge In Networks of Medical Research

Please send your comments, suggestions and bug reports to Roy Navon at:
For questions regarding your results, please include a link to your results page.