GOstat was created at:
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WEHI
Bioinformatics

Contact

Copyright 2004
Walter & Eliza Hall Institute
Supported by
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GOstatby Tim Beißbarth
beissbarth@wehi.edu.au

Find statistically overrepresented GO terms within a group of genes


Run GOstat:
  • Go to search form
    Computes GO statistics of a list of genes selected from a microarray.
  • GOstat Display
    You can store results from a previously run and view them here, either by uploading them as a file or putting them on a selected URL.
  • Upload Custom GO Annotations
    This allows you to upload your own GO annotation database and use it with GOstat.

Variants of GOstat:
  • Rank GOstat
    Takes input from all genes on microarray instead of using a fixed cutoff and uses ranks using a Wilcoxon test or either ranks or pvalues to score GOs using Kolmogorov-Smirnov statistics.
  • Gene Abundance GOstats
    Takes input from all genes on microarray and sums up the gene abundances for each GO to compute statistics.
  • Two list GOstat
    Compares GO statistics in two independent lists of genes, not necessarily one of them being the complete list the other list is sampled from.

Description:

The Gene-Ontology database (GO: http://www.geneontology.org) provides a useful tool to annotate and analyze the function of large numbers of genes. Modern experimental techniques, as e.g. DNA microarrays, often result in long lists of genes. To learn about the biology in this kind of data it is desirable to find functional annotation or Gene-Ontology groups which are highly represented in the data. This program (GOstat) should help in the analysis of such lists and will provide statistics about the GO terms contained in the data and sort the GO annotations giving the most representative GO terms first.

View Example

References (please cite):

GOstat: Find statistically overrepresented Gene Ontologies within a group of genes
Beissbarth T, Speed TP
Bioinformatics, 6.2004; 20(9): 1464-1465.

View Poster (ISMB 2003):
GOstat - Find statistically overrepresented Gene Ontologies within a group of genes

In case of problems contact beissbarth@wehi.edu.au.