Seurat (version 4.3.0.1)

AggregateExpression: Aggregated feature expression by identity class

Description

Returns aggregated (summed) expression values for each identity class

Usage

AggregateExpression(
  object,
  assays = NULL,
  features = NULL,
  return.seurat = FALSE,
  group.by = "ident",
  add.ident = NULL,
  slot = "data",
  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

Categories for grouping (e.g, ident, replicate, celltype); 'ident' by default

add.ident

(Deprecated) Place an additional label on each cell prior to pseudobulking (very useful if you want to observe cluster pseudobulk values, separated by replicate, for example)

slot

Slot(s) to use; if multiple slots are given, assumed to follow the order of 'assays' (if specified) or object's assays

verbose

Print messages and show progress bar

...

Arguments to be passed to methods such as CreateSeuratObject#'

Details

If slot is set to 'data', this function assumes that the data has been log normalized and therefore feature values are exponentiated prior to aggregating so that sum is done in non-log space. Otherwise, if slot is set to either 'counts' or 'scale.data', no exponentiation is performed prior to aggregating If return.seurat = TRUE and slot is not 'scale.data', aggregated values are placed in the 'counts' slot of the returned object and the log of aggregated values are placed in the 'data' slot. For the ScaleData is then run on the default assay before returning the object. If return.seurat = TRUE and slot is 'scale.data', the 'counts' slot is left empty, the 'data' slot is filled with NA, and 'scale.data' is set to the aggregated values.

Examples

data("pbmc_small")
head(AggregateExpression(object = pbmc_small))