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enables rapid, interactive and easy-to-use biological interpretation of microarray data from prokaryotes using Gene Ontology
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supports the analysis of microarray data from more than 20 well annotated prokaroytic species including important model organisms like Escherichia coli and Bacillus subtilis. In addition, many medical relevant pathogenic species are included like for example Pseudomonas aeruginosa, Clostridium tetani, Helicobacter pylory, Listeria monocytogenes, Mycobacterium tuberculosis and Staphylococcus aureus
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supports threshold value based and threshold value independent analysis of microarray data
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offers the most common statistical methods for the identification of Gene Ontology terms (GO nodes) which differ significantly in their gene expression profile from their environment
I) Threshold value based methods: Hypergeometric test and Fisher's exact test
II) Threshold value independent methods: Kolmogorov-Smirnov test, Student's t-test. Furthermore, unpaired Wilcoxon's test which also is threshold independent and - in addition - rank-based is provided by this tool.
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representation of results as a table with multiple sorting and search functionalities (supporting for example regular expressions). Download of results as a tab-delimited text file.
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interactive graphical representation of results as GO subgraph containing the significant GO nodes and their paths up to the root nodes comprising all parent nodes. The size and color of the nodes represents their p-values. Clicking on a node of interest shows it expression profile and the genes assigned to it. Download of results as a png or pdf image.
- direct access to external information resources
1) GO nodes are directly linked to the Amigo web interface of the GO database. This facilitates the retrieval of further information on the GO categories.
2) genes linked to the GO nodes of interest can be visualized as a table. They are directly linked to PRODORIC database providing an comprehensive overview on their regulatory interactions
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visualization of gene expression profile (expression value distribution) of GO nodes of interest compared to the expression profile of their environment (background distribution). Histograms are used for this purpose.
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recognition of alternative gene names in a strict priority order starting with the official gene short names. Subsequently - if necessary - the ordered locus numbers (ORF ID's) are taken into account and finally the synonyms. Redundant synonyms were removed before in order to avoid ambiguities.
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supports different types of microarray data such as expression ratios/log-ratios and probabilities of differential expression
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proof of validity of submitted microarray data, for example check for correct number format
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