GoSurfer was updated at 03/18/2007
Platforms: Windows 2000/XP


GoSurfer uses Gene Ontology (GO) information to analyze gene sets obtained from genome-wide computations or microarray analyses. GoSurfer is a graphical interactive data mining tool. It associates user input genes with GO terms and visualizes such GO terms as a hierarchical tree. Users can manipulate the tree output by various means, like setting heuristic thresholds or using statistical tests. Significantly important GO terms resulted from a statistical test can be highlighted. All related information are exportable either as texts or as graphics.







News & Updates:

09/01/2007: Editorial on Artificial Intelligence in Medicine reviews GoSurfer.

05/15/2007: Software update: GoSurfer takes gene clusters as input.

03/18/2007: Software update. New script downloadable at "Download" page.

08/08/2006: Application example: Gene expression analysis of bipolar disorder. Molecular Psychiatry 11, 965978.


04/05/2006: GoSurfer is cited by A Primer of Genome Science, published by Sinauer Associates, Inc.

03/03/2006: GO structure file is updated. Some new Gene Information Files are added.

06/30/2005: GoSurfer is rated as "the fastest Gene Ontology analysis tool" by Purvesh Khatri and Sorin Draghici's review article in Bioinformatics.

04/29/2004: A short tutorial is available. It can also be activated in the GoSurfer program by using the "Help->Online Tutorial" menu.

03/20/2004: The false discovery rate (FDR) for GO-term to gene-list association test can be calculated from menu "Analysis->FDR". Users can highlight the GO terms with small FDRs (q-values) from menu "Analysis->Highlight->Significance test: adjusting for multiple hypothesis testing".


Sheng Zhong and Dan Xie. Gene Ontology analysis in multiple gene clusters under multiple hypothesis testing framework.
Artificial Intelligence in Medicine 2007. 41:105-115 Abstract, PDF

Zhong S, Storch F, Lipan O, Kao MJ, Weitz C, Wong WH. GoSurfer:  a graphical interactive tool for comparative analysis of large gene sets in Gene Ontology space. Applied Bioinformatics 2004, 3(4): 1-5. Abstract, Technical report


For questions and suggestions, please contact:
Dan Xie, Dept of Bioengineering, University of Illinois and Urbana-Champaign

This site was last updated 11/23/07