Returns averaged expression values for each identity class
AverageExpression(
object,
assays = NULL,
features = NULL,
return.seurat = FALSE,
group.by = "ident",
add.ident = NULL,
slot = "data",
verbose = TRUE,
...
)
Returns a matrix with genes as rows, identity classes as columns.
If return.seurat is TRUE, returns an object of class Seurat
.
Seurat object
Which assays to use. Default is all assays
Features to analyze. Default is all features in the assay
Whether to return the data as a Seurat object. Default is FALSE
Categories for grouping (e.g, ident, replicate, celltype); 'ident' by default
(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(s) to use; if multiple slots are given, assumed to follow the order of 'assays' (if specified) or object's assays
Print messages and show progress bar
Arguments to be passed to methods such as CreateSeuratObject
If slot is set to 'data', this function assumes that the data has been log
normalized and therefore feature values are exponentiated prior to averaging
so that averaging is done in non-log space. Otherwise, if slot is set to
either 'counts' or 'scale.data', no exponentiation is performed prior to
averaging
If return.seurat = TRUE
and slot is not 'scale.data', averaged values
are placed in the 'counts' slot of the returned object and the log of averaged values
are placed in the 'data' slot. 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.
data("pbmc_small")
head(AverageExpression(object = pbmc_small))
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