Convert a SingleCellExperiment to a ReticulateMuData

Converts a SingleCellExperiment::SingleCellExperiment (possibly with alternative experiments attached via SingleCellExperiment::altExps()) to a ReticulateMuData.

The main SCE is mapped to the modality named main_modality. Each alternative experiment (accessed with SingleCellExperiment::altExpNames()) is mapped to its own modality using the altExp name as the key.

All matrix transfers are zero-copy (via sce_assay_to_scipy_csc()).

Usage

sce_to_reticulate_mudata(
  x,
  main_modality = "rna",
  assay = "counts",
  altexp_assay = NULL,
  obs = list(),
  obsm = list(),
  ...
)

Arguments

x

A SingleCellExperiment::SingleCellExperiment.

main_modality

Character string; name for the main SCE modality. Default: "rna".

assay

Character string; assay name to use as X in the main modality (passed to sce_to_anndata()). Default: "counts".

altexp_assay

Character string or NULL. Assay to use as X in each alternative experiment modality. If NULL (default) the first available assay is used for each altExp.

obs

Named list of additional columns to add to the modalities' obs data frames. Each element must be a vector/factor of length ncol(x). Forwarded to sce_to_anndata() for each modality.

obsm

Named list of embedding matrices (cells × dims) to attach to each modality's obsm. Forwarded to sce_to_anndata() for the main SCE.

...

Additional arguments forwarded to sce_to_anndata() for every modality (including altExps). Arguments that differ between modalities can be set via obs, obsm, etc., which only apply to the main modality.

Value

A ReticulateMuData wrapping a Python mudata.MuData.

See also

sce_to_anndata(), mae_to_reticulate_mudata(), ReticulateMuData

Examples

if (FALSE) { # \dontrun{
# ---- Minimal synthetic CITE-seq example ----
library(SingleCellExperiment)
library(Matrix)

set.seed(42)
n_cells <- 100; n_genes <- 500; n_proteins <- 30

rna_counts <- Matrix::rsparsematrix(n_genes, n_cells, density = 0.1,
                                    repr = "C")
adt_counts <- Matrix::rsparsematrix(n_proteins, n_cells, density = 0.5,
                                    repr = "C")

sce <- SingleCellExperiment(
  assays  = list(counts = rna_counts),
  colData = S4Vectors::DataFrame(cell_type = sample(c("T","B"), n_cells, TRUE))
)
rownames(sce) <- paste0("gene_", seq_len(n_genes))
colnames(sce) <- paste0("cell_", seq_len(n_cells))

adt_sce <- SingleCellExperiment(assays = list(counts = adt_counts))
rownames(adt_sce) <- paste0("protein_", seq_len(n_proteins))
colnames(adt_sce) <- colnames(sce)

SingleCellExperiment::altExp(sce, "adt") <- adt_sce

mdata <- sce_to_reticulate_mudata(sce, main_modality = "rna", assay = "counts")
print(mdata)
mdata$obs_names   # shared cell barcodes
mdata[["rna"]]    # ReticulateAnnData for RNA
mdata[["adt"]]    # ReticulateAnnData for ADT
} # }