Perform a robust estimation of the starting betas for the nmfLasso method
startingBetaEstimation(
x,
K = 3:10,
background_signature = NULL,
normalize_counts = TRUE,
nmf_runs = 10,
seed = NULL,
verbose = TRUE
)count matrix for a set of n patients and 96 trinucleotides.
numeric value (minimum 2) indicating the number of signatures to be discovered.
background signature to be used. If not provided, a warning is thrown and an initial value for it is estimated by NMF. If beta is not NULL, this parameter is ignored.
if true, the input count matrix x is normalize such that the patients have the same number of mutation.
number of iteration (minimum 1) of NMF to be performed for a robust estimation of starting beta. If beta is not NULL, this parameter is ignored.
Seed for reproducibility.
boolean; Shall I print all messages?
A list containing the starting beta values for each configuration of K.
data(background)
data(patients)
res = startingBetaEstimation(x=patients[1:100,],
K=3:5,
background_signature=background,
nmf_runs=1,
seed=12345)
#> Performing a robust estimation of the starting betas for the nmfLasso method...
#> Computing the initial values of beta by standard NMF...
#> Progress 33.333%...
#> Computing the initial values of beta by standard NMF...
#> Progress 66.667%...
#> Computing the initial values of beta by standard NMF...
#> Progress 100%...