To get the optimal results from this tool it requires two separate runs. First run the tool with default settings. Then consult the generated false discovery rate graph, and adjust the delta value used for plotting (it is also used for generating the list of significant genes) accordingly.
The random number selection is essential. If you would like to run the test several times, you might want to adjust the random number, since using the same random number should always give you exactly the same result. This also assists in reporting the results: mention the used the random number in the report, and somebody else could replicate your results.
Two images plotting the genes with delta limits on one graph and the delta values against the false discovery rate on the other. In addition, a data file containing the significant genes and their fold changes and p-values is generated.
This tool uses Bioconductor packages siggenes. Please cite the following articles:
Schwender, H., Krause, A., and Ickstadt, K. (2006). Identifying Interesting Genes with siggenes. RNews, 6(5), 45–50.
Tusher, V. G., Tibshirani, R., and Chu, G. (2001). Significance Analysis of Microarrays Applied to the Ionizing Radiation Response. Proceedings of the National Academy of Science, 98, 5116–5121.
This tool can be freely used for non-commercial purposes only. Commercial users need to license full Excel version of SAM from Stanford University.