Description Usage Arguments Details Value Examples
Returns aggregated (summed) expression values for each identity class
1 2 3 4 5 6 7 8 9 10 11 |
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 |
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.
Returns a matrix with genes as rows, identity classes as columns.
If return.seurat is TRUE, returns an object of class Seurat
.
1 2 | data("pbmc_small")
head(AggregateExpression(object = pbmc_small))
|
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