nexprs {scater} | R Documentation |
An efficient internal function that avoids the need to construct 'is_exprs_mat' by counting the number of expressed genes per cell on the fly.
nexprs(object, detection_limit = 0, exprs_values = "counts", byrow = FALSE, subset_row = NULL, subset_col = NULL)
object |
a |
detection_limit |
numeric scalar providing the value above which
observations are deemed to be expressed. Defaults to
|
exprs_values |
character scalar indicating whether the count data
( |
byrow |
logical scalar indicating if |
subset_row |
logical, integeror character vector indicating which rows (i.e. features/genes) to use. |
subset_col |
logical, integer or character vector indicating which columns (i.e., cells) to use. |
Setting subset_row
or subset_col
is equivalent to
subsetting object
before calling nexprs
, but more efficient
as a new copy of the matrix is not constructed.
If byrow=TRUE
, an integer vector containing the number of cells
expressing each feature, of the same length as the number of features in
subset_row
(all features in exprs_mat
if subset_row=NULL
).
If byrow=FALSE
, an integer vector containing the number of genes
expressed in each cell, of the same length as the number of cells specified in
subset_col
(all cells in exprs_mat
if subset_col=NULL
).
data("sc_example_counts") data("sc_example_cell_info") example_sce <- SingleCellExperiment( assays = list(counts = sc_example_counts), colData = sc_example_cell_info) nexprs(example_sce)[1:10] nexprs(example_sce, byrow = TRUE)[1:10]