as.cell_data_set | R Documentation |
cell_data_set
objectsConvert objects to Monocle3 cell_data_set
objects
as.cell_data_set(x, ...)
## S3 method for class 'Seurat'
as.cell_data_set(
x,
assay = DefaultAssay(object = x),
reductions = AssociatedDimReducs(object = x, assay = assay),
default.reduction = DefaultDimReduc(object = x, assay = assay),
graph = paste0(assay, "_snn"),
group.by = NULL,
...
)
x |
An object |
... |
Arguments passed to other methods |
reductions |
A vector of dimensional reductions add to the
|
default.reduction |
Name of dimensional reduction to use for clustering name |
graph |
Name of graph to be used for clustering results |
group.by |
Name of cell-level metadata column to use as identites; pass |
The Seurat
method utilizes
as.SingleCellExperiment
to transfer over expression
and cell-level metadata. The following additional information is also
transferred over:
Cell emebeddings are transferred over to the
reducedDims
slot. Dimensional reduction
names are converted to upper-case (eg. “umap” to “UMAP”) to
match Monocle 3 style
Feature loadings are transfered to
cds@reduce_dim_aux$gene_loadings
if present. NOTE: only the
feature loadings of the last dimensional reduction are transferred over
Standard deviations are added to
cds@reduce_dim_aux$prop_var_expl
if present. NOTE: only the
standard deviations of the last dimensional reduction are transferred over
Clustering information is transferred over in the following manner: if
cell-level metadata entries “monocle3_clusters” and
“monocle3_partitions” exist, then these will be set as the clusters
and partitions, with no nearest neighbor graph being added to the object;
otherwise, Seurat's nearest-neighbor graph will be converted to an
igraph
object and added to the cell_data_set
object along with Seurat's clusters. No partition information is added when
using Seurat's clsuters
A cell_data_set
object
as.SingleCellExperiment
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