Description Usage Arguments Details Value Examples
View source: R/calculateexpression.R
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.
1 2 
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
).
1 2 3 4 5 6  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]

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