## Statistics / Sample size calculations with an adapted BH method

### Description

Perform sample size calculations using an adapted Benjamini-Hochberg method.

### Parameters

- Phenodata column separating the samples into two groups
- Assume equal variances between groups (yes, no) [no]
- Distribution to calculate p-values from (normal, student) [normal]
- False discovery rate (0-1) [0.1]
- Image width (200...3200) [600]
- Image height (200...3200) [600]

### Details

This tool uses an adapted version of the Benjamini-Hochberg method to perform sample size calculations using a pilot data set. The necessary parameters, such as effect size and the proportion of differentially expressed genes, are estimated from the data. For more details, please see the referenced articles.

### Output

A plot and a text table showing estimates of average power as a function of sample size.

A set of quality control plots. For interpretation, please see the referenced CGHpower paper, and these evaluation data sets.

### References

Technical description of the method:

Ferreira et al. (2006) Approximate power and sample size calculations with the Benjamini-Hochberg method. Int J Biostat 2: Article8

An illustration with real and simulated microarray expression data:

Ferreira et al. (2006) Approximate sample size calculations with microarray data: an illustration.. Stat Appl Genet Mol Biol 5: Article25

The use of the method in the context of aCGH (CGHpower). Whereas the other two references are fairly technical, this one is written mostly for biologists:

Scheinin et al. (2010) CGHpower: exploring sample size calculations for chromosomal copy number experiments. BMC Bioinformatics 11: 331