biocLite("SingleCellExperiment")
biocLite("scran")
library(SingleCellExperiment)
library(scran)
list_of_sce <- list()
# Looping though the UMI_count 'split_factor' columns at a time
split_factor = 500
for(i in seq(1,ncols, split_factor)) {
  num_loop = floor(i / split_factor) + 1
  idx = ncols
  if (i + split_factor < ncols) {
  idx = i + split_factor
  }
  sce <- SingleCellExperiment(list(counts=UMI_count[, i : idx]))
  # Normalization of the dataset containing
  # heterogenous cell data (different cell types)
  clusters <- quickCluster(sce)
  sce <- computeSumFactors(sce, cluster=clusters)
  list_of_sce[[num_loop]] <- sce
}
cbind(list_of_sce)