compGoM {CountClust} | R Documentation |
This function takes the FitGoM
/maptpx fitted model
and computes log likelihood, BIC and null model loglikelihood
for the fitted GoM models.
compGoM(data, model)
data |
matrix on which GoM model is fitted (samples along rows, genes along columns) |
model |
|
compGoM_models a vector list that returns the BIC and loglikelihood
values for each of the fitted models in model
.
read.data <- function() { x <- tempfile() download.file(paste0("https://cdn.rawgit.com/kkdey/", "singleCellRNASeqMouseDeng2014", "/master/data/Deng2014MouseEsc.rda"), destfile = x, quiet = TRUE) z <- get(load((x))) return(z) } Deng2014MouseESC <-read.data() # Extract observed counts deng.counts <- Biobase::exprs(Deng2014MouseESC) # Import GoM fitting results data("MouseDeng2014.FitGoM") names(MouseDeng2014.FitGoM) compGoM(data = t(deng.counts), model = MouseDeng2014.FitGoM) compGoM(data = t(deng.counts), model = MouseDeng2014.FitGoM$clust_3)