GAME: a greedy approach for detection of mutual exclusivity analysis in cancer study


The GAME software was written in R language and can be downloaded here . After sourcing the files into R environment, one can apply the fGAME function for a mutation status matrix in R.

Usage

        fGAME(data,k=8,C1=0.95,C2=3,maxsize=8,mm=10,permutation=1000);

Arguments

• data: matrix of mutation status in which rows are samples and columns are gene variants, entries are mutation status (0 or 1)
• k: the maximum size of the ME set;
• C1: the tuning parameter alpha;
• C2: the tuning parameter xi;
• maxsize: a parameter in pre-selection procedure;
• mm: the gene size selected by pre-selection procedure;
• permutation: number of permutation replicates.

Output

• selected.me.set: the selected ME (mutually exclusive) set.
• p.value: p value for the selected ME set.

Example

A data example can be found here , read into R by
> data= read.table("data.txt")
or run this command in R:
>data=c(0,1,0,1,0,0,0,1,0,0,0,0,1,0,0,1,0,1,1,1,0,0,0,0,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,1,0,0,0,0,1,0,0,1,0,0,0,1,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,1,1,1,0,0,0,1,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,1,0,0,1,0,1,0,0,0,1,0,0,1,0,0,0,0,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,1,0,0,0,0,0,0,1,1,0,0,1,1,0,0,0,1,0,0,1,0,0,1,0,0,1,0,1,0,1,1,0,1,0,0,0)
> data=matrix(data, nrow=20)

Then run the fGAME function
> fGAME(data,k=8,C1=0.95,C2=3,maxsize=8,mm=10,permutation=1000)
$`selected.me.set`
[1] 1 2 4 3

$p.value
[1] 0.005