as.Seurat.cell_data_set | R Documentation |
Convert single cell experiment to Seurat
## S3 method for class 'cell_data_set'
as.Seurat(
x,
counts = "counts",
data = NULL,
assay = "RNA",
project = "cell_data_set",
loadings = NULL,
clusters = NULL,
...
)
loadings |
Name of dimensional reduction to save loadings to, if present;
defaults to first dimensional reduction present (eg.
|
clusters |
Name of clustering method to use for setting identity classes |
The cell_data_set
method for as.Seurat
utilizes the SingleCellExperiment
method of
as.Seurat
to handle moving over expression data, cell
embeddings, and cell-level metadata. The following additional information
will also be transfered over:
Feature loadings from cds@reduce_dim_aux$gene_loadings
will be
added to the dimensional reduction specified by loadings
or the name
of the first dimensional reduction that contains "pca" (case-insensitive) if
loadings
is not set
Monocle 3 clustering will be set as the default identity class. In addition, the Monocle 3 clustering will be added to cell-level metadata as “monocle3_clusters”, if present
Monocle 3 partitions will be added to cell-level metadata as “monocle3_partitions”, if present
Monocle 3 pseudotime calculations will be added to “monocle3_pseudotime”, if present
The nearest-neighbor graph, if present, will be converted to a
Graph
object, and stored as
“assay
_monocle3_graph”
as.Seurat.SingleCellExperiment
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