Create .cells Object from SingleCellExperiment Object

Converts a SingleCellExperiment (SCE) object into tinydenseR's .cells format. SCE is the standard Bioconductor container for single-cell data. Each sample's cells are extracted and saved as temporary RDS files.

Usage

get.cells.SCE(
  .sce.obj,
  .meta,
  .sample.var,
  .assay = "counts",
  .min.cells.per.sample = 10,
  .compress = FALSE,
  .verbose = TRUE
)

Arguments

.sce.obj: SingleCellExperiment object containing expression data in assays.
.meta: Data frame with sample-level metadata. Rownames must be sample IDs matching values in .sce.obj@colData[[.sample.var]]. Required for filtering valid samples.
.sample.var: Character: column name in colData(.sce.obj) identifying which sample each cell belongs to (e.g., "sample_id", "Sample").
.assay: Character: assay name to extract. Default "counts". Can also be "logcounts", "normcounts", or any assay in assayNames(.sce.obj).
.min.cells.per.sample: Integer: minimum cells required per sample. Default 10.
.compress: Logical: compress RDS files? Default FALSE for faster I/O.
.verbose: Logical: print progress messages? Default TRUE.

Value

Named list of file paths to temporary RDS files, one per sample. Only includes samples meeting minimum cell threshold and present in .meta.

Details

SingleCellExperiment is the Bioconductor standard for single-cell data, used by many analysis packages. This function extracts cells sample-by-sample and converts to sparse dgCMatrix format for memory-efficient storage.

The function verifies that colnames(.sce.obj) exist, as these are required for proper cell tracking.

Examples

if (FALSE) { # \dontrun{
# Load example data
trajectory_data <- fetch_trajectory_data()
sim_trajectory.meta <- trajectory_data$meta |>
  dplyr::select(Condition, Replicate, Sample) |>
  unique()
rownames(sim_trajectory.meta) <- sim_trajectory.meta$Sample
sim_trajectory <- trajectory_data$SCE

# Convert SCE directly to .cells format
cells <- get.cells.SCE(.sce.obj = sim_trajectory,
                       .meta = sim_trajectory.meta,
                       .sample.var = "Sample")

# Use in tinydenseR workflow
lm.obj <- setup.tdr.obj(.cells = cells,
                       .meta = sim_trajectory.meta,
                       .assay.type = "RNA")
} # }