## Copy number aberrations / Group tests for called copy number data

### Description

Statistical tests between two or more groups for called copy number data. The testing is recommended to be performed after running the Identify common regions from called aCGH data tool.

### Parameters

- Phenodata column separating the samples into two or more groups
- Test statistic (Chi-square, Wilcoxon, Kruskal-Wallis) [Chi-square]
- Number of permutations (...) [10000]
- Aberrations to test (losses, gains, both) [both]

### Details

Perform statistical testing between groups for differences in copy number aberrations. Three different test statistics are available for the p-value calculations. The significance of the p-values is evaluated by permuting the sample groups, and a false discovery rate is calculated. At least 10,000 permutations are recommended for final calculations, and this will require a significant amount of time. Testing can be performed only for gains/losses, or both.

### Output

The input table appended with loss/gain/amplification frequencies for the different groups, along with p-values and false discovery rates.

A plot showing frequencies of gains (blue) and/or losses (red) together with the -log10 tranformed false discovery rate (FDR, right scale).

### References

Wiel et al. (2005) CGHMultiArray: exact p-values for multi-array comparative genomic hybridization data. Bioinformatics 21: 3193-3194