There are two scenarios where Gitools can perform a mutex or co-oc test:
Data Matrix: A file with either binary (i.e. presence/absence), categorical (i.e. alteration status) or continuous (i.e. an expression matrix) data.
Things to consider
The testThe test is based on weighted permutations assessing the deviation of the observed coverage (number of columns with a signal) compared to expected obtained by permuting events, maintaining the number of events per row and weighted permutations for columns.
Data usedThe column weights, used for the permutations are based on the “events” (Data Events) in each column including hidden rows. The more rows that are included, the more accurate the weight parameter, therefore if you are performing the test on a dataset that contains only is a subset and rows are missing (e.g. not all genes present) this parameter may be inaccurate and the end result may be inaccurate.
The result of a test will yield the following values:
- Z-score: Zscore shows the deviation of the observed coverage (number of columns with a signal) compared to expected, obtained by permuting events, maintaining the number of events per row and weighted permutations for columns.
- MutEx p-value: Significance p-value of mutual exclusivity derived from the Z-score
- Co-occurrence p-value: Significance p-value of co-occurrence derived from the Z-Score