simulateGenes: Generates data from the TiMEx model

In cbg-ethz/TiMEx: Finding Mutually Exclusive Groups of Alterations in Cancer Datasets

Description

simulateGenes returns a list containing a binary matrix simulated from the TiMEx model, for given lambdas (exponential rates), mu (intensity of mutual exclusivity), and N (sample size).

Usage

simulateGenes(lambdas, mu, N)

Arguments

lambdas	vector of exponential rates (positive real numbers). The length of the vector equals the number of simulated genes.
mu	intensity of mutual exclusivity (real number between 0 and 1). Default is 1 (perfect mutual exclusivity).
N	sample size (positive integer).

Details

This function needs permutations in order to run.

For details on how the values of the exponential rates correspond to frequencies, see References below.

Value

list consisting of:

• genes the simulated dataset, as a binary matrix.

• genoMat the matrix with genotype probabilities, from which the dataset was simulated. This matrix has as many dimensions as number of genes, i.e. 2x2x...x2. For each dimension, the first position corresponds to the probability of observing a 0 for that gene, and the second position corresponds to the probability of observing an 1. For example, in the case of 4 genes, the probability of observing the null genotype (0000) is given by genoMat[1,1,1,1]; the probability of observing the genotype (1011) is given by genoMat[2,1,2,2]; the probability of observing the genotype (1111) is given by genoMat[2,2,2,2]. The entries of this matrix are nonnegative and sum up to 1.

Author(s)

Simona Cristea, [e-mail]

References

Constantinescu et al.: TiMEx: A Waiting Time Model for Mutually Exclusive Cancer Alterations. Bioinformatics (2015).

See Also

the wrapper function TiMEx for identifying mutually exclusive groups in a binary dataset with the TiMEx model, ovarian, breast, and gbmDendrix for examples of biological large cancer datasets.

Examples

simGenes<-simulateGenes(c(0.5,1,0.3),0.8,4000)

cbg-ethz/TiMEx documentation built on May 13, 2019, 1:50 p.m.