Cepo {Cepo} | R Documentation |
ExprsMat accepts various matrix objects, including DelayedArray and HDF5Array for out-of-memory computations. See vignette.
Cepo( exprsMat, cellTypes, minCells = 20, minCelltype = 3, exprsPct = NULL, logfc = NULL, computePvalue = NULL, variability = "CV", method = "weightedMean", weight = c(0.5, 0.5), workers = 1L, block = NULL, ... )
exprsMat |
Expression matrix where columns denote cells and rows denote genes |
cellTypes |
Vector of cell type labels |
minCells |
Integer indicating the minimum number of cells required within a cell type |
minCelltype |
Integer indicating the minimum number of cell types required in each batch |
exprsPct |
Percentage of lowly expressed genes to remove. Default to NULL to not remove any genes. |
logfc |
Numeric value indicating the threshold of log fold-change to use to filter genes. |
computePvalue |
Whether to compute p-values using bootstrap test. Default to NULL to not make computations. Set this to an integer to set the number of bootstraps needed (recommend to be at least 100). |
variability |
A character indicating the stability measure (CV, IQR, MAD, SD). Default is set to CV. |
method |
Character indicating the method for integration the two stability measures. By default this is set to 'weightedMean' with equal weights. |
weight |
Vector of two values indicating the weights for each stability measure. By default this value is c(0.5, 0.5). |
workers |
Number of cores to use. Default to 1, which invokes
|
block |
Vector of batch labels |
... |
Additional arguments passed to |
Returns a list of key genes.
library(SingleCellExperiment) data('cellbench', package = 'Cepo') cellbench cepoOutput <- Cepo(logcounts(cellbench), cellbench$celltype) cepoOutput