Statistics / One sample tests


Runs a statistical test designed to find the genes that are statistically significantly differentially expressed. These are the genes that display a mean expression that is significantly different from 0.



Every gene's mean expression value is compared to the assumed mean. The resulting p-value can be corrected for multiple tests. The genes that have an adjusted p-value smaller than the specified cut-off are returned. By default the chips are scaled to the same mean before running the test, but this can be avoided by the setting the parameter "Scale to the same mean" to no.

Multiple testing correction options are Bonferroni, Holm, and Hochberg for family-wise error rate (FWER) and Benjamini-Hochberg and Benjamini-Yakutieri for false discovery rate (FDR). Of these Bonferroni is the most conservative, returning the smallest number of genes, and FDR-based adjustments are less conservative, and return more genes.

If you want to get a p-value for every single gene in your data set, set the p-value cut-off to 1. This should return a new gene list of equal length to the original one.


A list of genes with expression values and p-values.