compute_supercells: Computes super-cells for the Exact, Approximate super-cells...
In mariiabilous/SuperCellBM:

Computes super-cells for the Exact, Approximate super-cells and for Subsampling and Random grouping for gammas in "gamma.seq" and for different Random seeds "seed.seq"

compute_supercells(
  sc.GE,
  gamma.seq,
  ToComputeSC,
  filename = "initial",
  data.folder = "./data",
  n.var.genes = 1000,
  k.knn = 5,
  n.pc = 10,
  approx.N = 1000,
  fast.pca = TRUE,
  genes.use = NULL,
  genes.exclude = NULL,
  seed.seq = c(12345, 111, 19, 42, 7),
  verbose = FALSE
)

`sc.GE`	single-cell gene expression matrix with genes as rows and cells as columns
`gamma.seq`	a vector of graining levels (i.e., `c(1, 5, 10, 50, 100, 200)`)
`ToComputeSC`	a bool flag to indicate whether to compute super-cells (if TRUE) or load (if FALSE) (if was previously computed and saved)
`filename`	filename to save/load the resulting list of super-cells
`data.folder`	path to the data folder of a certain analysis, usualy in a format './data/project_name/'
`n.var.genes`	`"n.var.genes"` parameter of SuperCell function SCimplify
`k.knn`	`"k.knn"` parameter of SuperCell function SCimplify
`n.pc`	`"n.pc"` parameter of SuperCell function SCimplify, can be a number, then 1:n.pc PC will be used to compute super-cells or a specific vector of PC to use (e.g., 2:15, c(2, 5, 6, 19))
`approx.N`	`"approx.N"` parameter of SuperCell function SCimplify
`fast.pca`	whethre to use fast PCA implementation from ilbra package (default TRUE)
`genes.use`	`"genes.use"` parameter of SuperCell function SCimplify. A specific genes set to use for computing super-cells, if provided, then parameter `"n.var.genes"` will be omitted, if not provided, top `"n.var.genes"` most variable genes will be used
`genes.exclude`	genes exclude from the gene set used for the computation of super-cells (e.g., a vector containing mito genes or ribo genes)
`seed.seq`	a vector of Random seeds (used for the Approximate coarse-graining, Subsampling and Random grouping)