sumCountsAcrossFeatures {scater}R Documentation

Sum counts across feature sets

Description

Sum together expression values (by default, counts) for each feature set in each cell.

Usage

sumCountsAcrossFeatures(x, ...)

## S4 method for signature 'ANY'
sumCountsAcrossFeatures(
  x,
  ids,
  subset_row = NULL,
  subset_col = NULL,
  average = FALSE,
  BPPARAM = SerialParam()
)

## S4 method for signature 'SummarizedExperiment'
sumCountsAcrossFeatures(x, ..., exprs_values = "counts")

aggregateAcrossFeatures(x, ids, ..., use_exprs_values = "counts")

Arguments

x

For sumCountsAcrossFeatures, a numeric matrix of counts containing features in rows and cells in columns. Alternatively, a SummarizedExperiment object containing such a count matrix.

For aggregateAcrossFeatures, a SummarizedExperiment containing a count matrix.

...

For the sumCountsAcrossFeatures generic, further arguments to be passed to specific methods.

For the SummarizedExperiment method, further arguments to be passed to the ANY method.

For aggregateAcrossFeatures, further arguments to be passed to sumCountsAcrossFeatures.

ids

A factor of length nrow(x), specifying the set to which each feature in x belongs.

Alternatively, a list of integer or character vectors, where each vector specifies the indices or names of features in a set.

subset_row

An integer, logical or character vector specifying the features to use. Defaults to all features.

subset_col

An integer, logical or character vector specifying the cells to use. Defaults to all cells with non-NA entries of ids.

average

Logical scalar indicating whether the average should be computed instead of the sum.

BPPARAM

A BiocParallelParam object specifying whether summation should be parallelized.

exprs_values

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).

use_exprs_values

A character or integer vector specifying the assay(s) of x containing count matrices.

Details

This function provides a convenient method for aggregating counts across multiple rows for each cell. Several possible applications are listed below:

The behaviour of this function is equivalent to that of rowsum. However, this function can operate on any matrix representation in object, and can do so in a parallelized manner for large matrices without resorting to block processing.

If ids is a factor, any NA values are implicitly ignored and will not be considered or reported. This may be useful, e.g., to remove undesirable feature sets by setting their entries in ids to NA.

Setting average=TRUE will compute the average in each set rather than the sum. This is particularly useful if x contains expression values that have already been normalized in some manner, as computing the average avoids another round of normalization to account for differences in the size of each set.

Value

For sumCountsAcrossFeatures, a count matrix is returned with one row per level of ids. In each cell, counts for all features in the same set are summed together. Rows are ordered according to levels(ids).

For aggregateAcrossFeatures, a SummarizedExperiment of the same class as x is returned, containing summed matrices generated by sumCountsAcrossFeatures on all assays in use_exprs_values. Row metadata is retained for the first instance of a feature from each set in ids.

Author(s)

Aaron Lun

Examples

example_sce <- mockSCE()
ids <- sample(LETTERS, nrow(example_sce), replace=TRUE)
out <- sumCountsAcrossFeatures(example_sce, ids)
str(out)

[Package scater version 1.16.2 Index]