# Introduction to Rediscover

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.

## Installation

Rediscover can be installed from CRAN repository:

install.packages("Rediscover")

## Introduction

The package library has two main parts:

• Estimation of the probabilities $$p_ {ij}$$ that gene i is mutated in sample j -assuming conditional independence between genes and samples-.
• Estimation of p-values using the Poisson-Binomial distribution, using the previous probabilities and the number of samples in which two genes are co-mutated. The corresponding null hypothesis $$H_0$$ is that the mutational status of both genes is independent of each other.

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.