Seurat (version 5.0.3)

AggregateExpression: Aggregated feature expression by identity class

Description

Returns summed counts ("pseudobulk") for each identity class.

Usage

AggregateExpression(
  object,
  assays = NULL,
  features = NULL,
  return.seurat = FALSE,
  group.by = "ident",
  add.ident = NULL,
  normalization.method = "LogNormalize",
  scale.factor = 10000,
  margin = 1,
  verbose = TRUE,
  ...
)

Value

Returns a matrix with genes as rows, identity classes as columns. If return.seurat is TRUE, returns an object of class Seurat.

Arguments

object

Seurat object

assays

Which assays to use. Default is all assays

features

Features to analyze. Default is all features in the assay

return.seurat

Whether to return the data as a Seurat object. Default is FALSE

group.by

Category (or vector of categories) for grouping (e.g, ident, replicate, celltype); 'ident' by default To use multiple categories, specify a vector, such as c('ident', 'replicate', 'celltype')

add.ident

(Deprecated). Place an additional label on each cell prior to pseudobulking

normalization.method

Method for normalization, see NormalizeData

scale.factor

Scale factor for normalization, see NormalizeData

margin

Margin to perform CLR normalization, see NormalizeData

verbose

Print messages and show progress bar

...

Arguments to be passed to methods such as CreateSeuratObject

Details

If return.seurat = TRUE, aggregated values are placed in the 'counts' layer of the returned object. The data is then normalized by running NormalizeData on the aggregated counts. ScaleData is then run on the default assay before returning the object.

Examples

if (FALSE) {
data("pbmc_small")
head(AggregateExpression(object = pbmc_small)$RNA)
head(AggregateExpression(object = pbmc_small, group.by = c('ident', 'groups'))$RNA)
}