## Copy number aberrations / GO enrichment for called gene copy numbers

### Description

Performs a statistical test for enrichment of GO terms in frequently aberrated genes. The input should be the result file from the tool "Detect genes from called copy number data".

### Parameters

- Type of aberrations to check (losses, gains, amplifications, gains and amplifications, all aberrations) [all aberrations]
- Aberration frequency threshold (0-1) [0.5]
- Ontology category (all, biological process, molecular function, cellular component) [biological process]
- P-value threshold (0-1) [0.05]
- Minimum population (1-1000000) [2]
- Conditional testing (yes, no) [yes]
- P-value adjustment method (none, BH, BY) [BH]
- Search for over or under-represented genes (under, over) [over]

### Details

This tool takes a gene-based copy number data set produced by the tool "Detect genes from called copy number data". The genes with more frequent aberrations than the specified threshold are selected from the list, and a hypergeometric test is used to check for over-represented (or under-represented) GO categories relative to the whole list of genes. The type of aberrations can include losses, gains, amplifications, gains+amplifications, or all aberrations (gains+losses+amplifications). Analysis can be restricted to GO terms which have a minimum, user-specified number of genes mapped to them (by default 2).

The default behavior is that in order to avoid the identification of directly related GO terms with considerable overlap of genes, this tool uses a method which conditions on all child terms that are themselves significant at a specified p- value cutoff. First the leaves of the graph (those terms with no child terms) are tested. All genes annotated at significant children are then removed before testing the parent terms. This continues until all terms have been tested. It is also possible to run the tests unconditional by setting the appropriate parameter. In that case it is also possible to apply multiple testing correction.

### Output

Output is a text file and an HTML file with a list of significant categories.