Computes the probability distributions of cell frequencies, by calling cellfrequency_pdf for each mutation separately.
computeCellFrequencyDistributions(dm, max_PM=6, p, min_CF=0.1, ploidy = 2, nc = 1, v = T)Matrix in which each row corresponds to a mutation. Has to contain at least the following column names: chr - the chromosome on which each mutation is located; startpos - the position of each mutation; AF_Tumor - the allele-frequency of each mutation; PN_B - the count of the B-allele in normal cells (binary variable: 1 if the mutation is a germline variant, 0 if somatic).
Upper threshold for the number of amplicons per mutated cell (default: 6). See also cellfrequency_pdf.
Precision with which subpopulation size is predicted, a small value reflects a high resolution and can lead to a higher number of predicted subpopulations.
Lower boundary for the prevalence of a mutated cell (default: 0.1).
The background ploidy of the sequenced sample (default: 2). Changing the value of this parameter is not recommended. Dealing with cell lines or tumor biopsies of very high (>=0.95) tumor purity is a necessary but not sufficient condition to change the value of this parameter.
The number of nodes to be forked to run R in parallel.
Give a more verbose output.
List with three fields:
The cellular frequencies for which probabilities are computed.
Matrix in which each row corresponds to a point mutation and each column corresponds to a cellular frequency. Each value \(densities[i,j]\) represents the probability that mutation \(i\) is present in a fraction \(freq[j]\) of cells.
The input matrix with column \(f\) updated according to the cellular frequency that best explains the observed allele frequency and copy number.