An optimized method for identifying mutually
exclusive genomic events. Its main contribution is a
statistical analysis based on the Poisson-Binomial
distribution that takes into account that some samples
are more mutated than others. See [Canisius, Sander, John WM Martens,
and Lodewyk FA Wessels. (2016) "A novel independence test for
somatic alterations in cancer shows that
biology drives mutual exclusivity but chance explains
most co-occurrence." Genome biology 17.1 : 1-17.
We present Rediscover, an R package to identify mutually exclusive genomic events. It reimplements a privious R package (Discover) whose main contribution is a statistical analysis based on the Poisson-Binomial distribution that takes into account that some samples are more mutated than others. Rediscover is much faster than the discover implementation.
Rediscover can be installed from CRAN repository:
install.packages("Rediscover")
The package library has two main parts:
The second step is the estimation of the p-values using these probabilities and the number of samples where two genes are co-altered. Rediscover offers different functions depending on the desired study:
getMutex if the user wants to evaluate if genes are mutually exclusive.getMutexAB if the user wants to evaluate if genes are mutually exclusive with respect to another event (amplifications, deletions, etc...)getMutexGroup will be used when the user wants to obtain the probability that a certain group of genes being mutually exclusive. Unlike the getMutex function, in this case the users introduces the set of genes of interest.Rediscover also provides a function to integrate its usage with maftools and TCGAbiolinks. Specifically, we added to the function somaticInteractions from maftools our analyses based on the Poisson-Binomial distribution resulting in a new function called discoversomaticInteractions.