Generate factorized matrices showing each feature's influence on the celda_G model clustering
# S3 method for celda_G
factorizeMatrix(celda.mod, counts, type = c("counts",
"proportion", "posterior"))Object return from celda_C function
A numeric count matrix
A character vector containing one or more of "counts", "proportions", or "posterior". "counts" returns the raw number of counts for each entry in each matrix. "proportions" returns the counts matrix where each vector is normalized to a probability distribution. "posterior" returns the posterior estimates which include the addition of the Dirichlet concentration parameter (essentially as a pseudocount).