ruvSimulate {scMerge} | R Documentation |
This function is designed to generate Poisson-random-variable data matrix to test on the internal algorithms of scMerge. It does not represent real biological situations and it is not intended to be used by end-users.
ruvSimulate(m = 100, n = 5000, nc = floor(n/2), nCelltypes = 3, nBatch = 2, k = 20, lambda = 0.1, sce = FALSE)
m |
Number of observations |
n |
Number of features |
nc |
Number of negative controls |
nCelltypes |
Number of cell-types |
nBatch |
Number of batches |
k |
Number of unwanted factors in simulation |
lambda |
Rate parameter for random Poisson generation |
sce |
If |
If sce
is FALSE, then the output is a list consists of
Y, expression matrix generated through Poisson random variables,
ctl, a logical vector indicating the control genes,
M, replicate mapping matrix,
cellTypes, a vector indicating simulated cell types
batch, a vector indicating simulated batches
if sce
is TRUE, a SingleCellExperiment wrapper will be applied on all above simulated objects.
set.seed(1) L = ruvSimulate(m = 200, n = 1000, nc = 200, nCelltypes = 3, nBatch = 2, lambda = 0.1, k = 10, sce = TRUE) print(L) example <- scMerge(sce_combine = L, ctl = paste0('gene', 1:500), cell_type = L$cellTypes, ruvK = 10, assay_name = 'scMerge') scater::plotPCA(L, colour_by = 'cellTypes', shape = 'batch', run_args = list(exprs_values = 'logcounts')) scater::plotPCA(example, colour_by = 'cellTypes', shape = 'batch', run_args = list(exprs_values = 'scMerge'))