numDetectedAcrossCells: Number of detected expression values per group of cells

In LTLA/scuttle: Single-Cell RNA-Seq Analysis Utilities

Number of detected expression values per group of cells

Description

Computes the number of detected expression values (by default, defined as non-zero counts) for each feature in each group of cells. This function is deprecated: use summarizeAssayByGroup instead.

Usage

numDetectedAcrossCells(x, ...)

## S4 method for signature 'ANY'
numDetectedAcrossCells(
  x,
  ids,
  subset.row = NULL,
  subset.col = NULL,
  store.number = "ncells",
  average = FALSE,
  threshold = 0,
  BPPARAM = SerialParam(),
  subset_row = NULL,
  subset_col = NULL,
  store_number = NULL,
  detection_limit = NULL
)

## S4 method for signature 'SummarizedExperiment'
numDetectedAcrossCells(x, ..., assay.type = "counts", exprs_values = NULL)

Arguments

x	A numeric matrix of counts containing features in rows and cells in columns. Alternatively, a SummarizedExperiment object containing such a count matrix.
...	For the generic, further arguments to pass to specific methods. For the SummarizedExperiment method, further arguments to pass to the ANY method.
ids	A factor specifying the group to which each cell in x belongs. Alternatively, a DataFrame of such vectors or factors, in which case each unique combination of levels defines a group.
subset.row	An integer, logical or character vector specifying the features to use. If NULL, defaults to all features. For the SingleCellExperiment method, this argument will not affect alternative Experiments, where aggregation is always performed for all features (or not at all, depending on use_alt_exps).
subset.col	An integer, logical or character vector specifying the cells to use. Defaults to all cells with non-NA entries of ids.
store.number	String specifying the field of the output colData to store the number of cells in each group. If NULL, nothing is stored.
average	Logical scalar indicating whether the proportion of non-zero counts in each group should be computed instead.
threshold	A numeric scalar specifying the threshold above which a gene is considered to be detected.
BPPARAM	A BiocParallelParam object specifying whether summation should be parallelized.
subset_row, subset_col, detection_limit, store_number, exprs_values	Soft-deprecated equivalents of the arguments above.
assay.type	A string or integer scalar specifying the assay of x containing the matrix of counts (or any other expression quantity that can be meaningfully summed).

Value

A SummarizedExperiment is returned containing a count matrix in the first assay. Each column corresponds to group as defined by a unique level or combination of levels in ids. Each entry of the matrix contains the number of cells with detected expression for a feature and group. The identities of the levels for each column are reported in the colData. If average=TRUE, the assay is instead a numeric matrix containing the proportion of detected values.

Author(s)

Aaron Lun

See Also

sumCountsAcrossCells, which computes the sum of counts within a group.

Examples

example_sce <- mockSCE()

ids <- sample(LETTERS[1:5], ncol(example_sce), replace=TRUE)
bycol <- numDetectedAcrossCells(example_sce, ids)
head(bycol)

LTLA/scuttle documentation built on March 9, 2024, 11:16 a.m.