## Statistics / One sample tests

### Description

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.
### Parameters

- Test type (t-test, Wilcoxon rank sum test) [t-test]
- Scale to the same mean (yes, no) [yes]
- Method of multiple testing correction (none, Bonferroni, Holm, Hochberg, BH, BY) [BH]
- P-value cut-off (0...1) [0.05]
- Assumed mean of the data (-100000...100000) [0]

### Details

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.

### Output

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