| 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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