Returns averaged expression values for each identity class.
AverageExpression(
object,
assays = NULL,
features = NULL,
return.seurat = FALSE,
group.by = "ident",
add.ident = NULL,
layer = "data",
slot = deprecated(),
verbose = TRUE,
...
)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
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')
(Deprecated). Place an additional label on each cell prior to pseudobulking
Layer(s) to use; if multiple layers are given, assumed to follow the order of 'assays' (if specified) or object's assays
(Deprecated). Slots(s) to use
Print messages and show progress bar
Arguments to be passed to methods such as CreateSeuratObject
Returns a matrix with genes as rows, identity classes as columns.
If return.seurat is TRUE, returns an object of class Seurat.
If layer 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 layer is set to
either 'counts' or 'scale.data', no exponentiation is performed prior to averaging.
If return.seurat = TRUE and layer is not 'scale.data', averaged values
are placed in the 'counts' layer of the returned object and 'log1p'
is run on the averaged counts and placed in the 'data' layer ScaleData
is then run on the default assay before returning the object.
If return.seurat = TRUE and layer is 'scale.data', the 'counts' layer contains
average counts and 'scale.data' is set to the averaged values of 'scale.data'.
data("pbmc_small")
head(AverageExpression(object = pbmc_small)$RNA)
#> 6 x 3 sparse Matrix of class "dgCMatrix"
#> g0 g1 g2
#> MS4A1 . 2.083443 171.6152
#> CD79B 10.814657 17.548842 152.1344
#> CD79A . 11.618333 215.0869
#> HLA-DRA 37.105857 405.850522 1158.0852
#> TCL1A . 3.463203 142.0748
#> HLA-DQB1 3.968254 45.353183 169.2762
head(AverageExpression(object = pbmc_small, group.by = c('ident', 'groups'))$RNA)
#> 6 x 6 sparse Matrix of class "dgCMatrix"
#> g0_g1 g0_g2 g1_g1 g1_g2 g2_g1 g2_g2
#> MS4A1 . . 3.720434 . 83.27443 269.7716
#> CD79B 12.32353 8.928571 16.783660 18.522712 80.07761 232.1975
#> CD79A . . 14.204794 8.326474 174.12523 260.5998
#> HLA-DRA 44.81837 27.465213 473.313733 319.988254 1217.90859 1091.6148
#> TCL1A . . 6.184292 . 60.19691 233.0502
#> HLA-DQB1 . 8.928571 51.863218 37.067684 170.88236 167.4915