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Convert objects to Monocle3 cell_data_set objects

Source: R/sw_monocle3.R
as.cell_data_set.Rd

Convert objects to Monocle3 cell_data_set objects

Usage

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,
  ...
)

Arguments

x

An object

...

Arguments passed to other methods

assay

Assays to convert

reductions

A vector of dimensional reductions add to the cell_data_set object; defaults to all dimensional reductions calculated from assay and all global dimensional reductions

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

Value

A cell_data_set object

Details

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

See also

as.SingleCellExperiment