Simulate a simple matrix or SingleCellExperiment to test internals of scMerge

Source: R/ruvSimulate.R

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
)

Arguments

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 TRUE, returns a SingleCellExperiment object

Value

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.

Examples

set.seed(1)
L = ruvSimulate(m = 200, n = 1000, nc = 200, 
nCelltypes = 3, nBatch = 2, lambda = 0.1, k = 10, sce = TRUE)
print(L)
#> class: SingleCellExperiment 
#> dim: 1000 200 
#> metadata(1): M
#> assays(2): counts logcounts
#> rownames(1000): gene1 gene2 ... gene999 gene1000
#> rowData names(0):
#> colnames(200): cell1 cell2 ... cell199 cell200
#> colData names(2): cellTypes batch
#> reducedDimNames(0):
#> mainExpName: NULL
#> altExpNames(0):
example <- scMerge(sce_combine = L,
                      ctl = paste0('gene', 1:500),
                      cell_type = L$cellTypes,
                      ruvK = 10,
                      assay_name = 'scMerge')
#> Dimension of the replicates mapping matrix: 
#> [1] 200   3
#> Step 2: Performing RUV normalisation. This will take minutes to hours. 
#> scMerge complete!
L = scater::runPCA(L, exprs_values = "logcounts")                      
scater::plotPCA(L, colour_by = 'cellTypes', shape = 'batch')


example = scater::runPCA(example, exprs_values = 'scMerge')                                       
scater::plotPCA(example, colour_by = 'cellTypes', shape = 'batch')