Calculate log lileklihood for the celda Cell and Gene clustering model, given a set of cell / gene cluster assignments

Calculate log lileklihood for the celda Cell and Gene clustering model, given a set of cell / gene cluster assignments

calculateLoglikFromVariables.celda_CG(counts, sample.label, z, y, K, L, alpha,
  beta, delta, gamma)

Arguments

counts	Integer matrix. Rows represent features and columns represent cells.
sample.label	Vector or factor. Denotes the sample label for each cell (column) in the count matrix.
z	Numeric vector. Denotes cell population labels.
y	Numeric vector. Denotes feature module labels.
K	Integer. Number of cell populations.
L	Integer. Number of feature modules.
alpha	Numeric. Concentration parameter for Theta. Adds a pseudocount to each cell population in each sample. Default 1.
beta	Numeric. Concentration parameter for Phi. Adds a pseudocount to each feature module in each cell population. Default 1.
delta	Numeric. Concentration parameter for Psi. Adds a pseudocount to each feature in each module. Default 1.
gamma	Numeric. Concentration parameter for Eta. Adds a pseudocount to the number of features in each module. Default 1.
...	Additional parameters.

Examples

celda.sim = simulateCells(model="celda_CG")
loglik = calculateLoglikFromVariables(celda.sim$counts, model="celda_CG",
                                      sample.label=celda.sim$sample.label,
                                      z=celda.sim$z, y=celda.sim$y,
                                      K=celda.sim$K, L=celda.sim$L,
                                      alpha=celda.sim$alpha, beta=celda.sim$beta,
                                      gamma=celda.sim$gamma, delta=celda.sim$delta)