diffDriver model only for binary phenotype, assuming bmr the same across samples.

This function uses the model as cmodel.frac, but generalizes to take more than 1 functional categories. This model is applied on data of a single gene. This should give the same results as ddmodel_binary defined above.

ddmodel_binary_simple(mut, e, bmr, fe)

Arguments

mut

a matrix of mutation status 0 or 1

e

a vector,phenotype of each sample, should match the columns of mut and bmr

bmr

a matrix, background mutation rate of each sample at each mutation (log scale), as we assume bmr the same across samples, only the first column will be used.

fe,

a vector, increased mutation rate at each mutation, due to functional effect (log scale), should match the rows of mut and bmr