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Load multiple 10x CellRanger h5 files into a single SingleCells

load_multi_tenx_h5.Rd

Takes the result of prescan_tenx_h5_files() and loads all inputs into a single experiment with global gene QC and sequential cell indexing. The feature space is determined by the prescan (intersection or union of gene ids).

Usage

load_multi_tenx_h5(
  object,
  prescan_result,
  sc_qc_param = params_sc_min_quality(),
  streaming = 1L,
  batch_size = 1000L,
  max_genes_in_memory = 2000L,
  cell_batch_size = 100000L,
  .verbose = TRUE
)

Arguments

object

SingleCells class.

prescan_result

Output of prescan_tenx_h5_files().

sc_qc_param

List. Output of params_sc_min_quality().

streaming

Integer. CSR-to-CSC conversion mode. 0L -> in-memory, 1L -> light streaming, 2L -> heavy streaming with memory upper boundaries. Defaults to 1L.

batch_size

Integer. Cell batch size when streaming = 1L. Defaults to 1000L.

max_genes_in_memory

Integer. Maximum genes held in memory at once when streaming = 2L. Defaults to 2000L.

cell_batch_size

Integer. Cell batch size when streaming = 2L. Defaults to 100000L.

.verbose

Boolean.

Value

The class with updated shape and populated DuckDB.

Examples

# two 10x h5 files into one experiment
files <- c(a = tempfile(fileext = ".h5"), b = tempfile(fileext = ".h5"))
for (i in seq_along(files)) {
  data <- generate_single_cell_test_data(
    syn_data_params = params_sc_synthetic_data(
      n_cells = 200L,
      n_genes = 40L
    ),
    seed = i
  )
  write_tenx_h5_sc(
    f_path = files[i],
    counts = data$counts,
    barcodes = data$obs$cell_id,
    features = data.table::data.table(
      id = data$var$gene_id,
      name = data$var$ensembl_id,
      feature_type = "Gene Expression"
    )
  )
}
scan_res <- prescan_tenx_h5_files(h5_paths = files, .verbose = FALSE)

dir_data <- tempfile("sc_multi_tenx")
dir.create(dir_data, recursive = TRUE)
sc <- load_multi_tenx_h5(
  object = SingleCells(dir_data = dir_data),
  prescan_result = scan_res,
  sc_qc_param = params_sc_min_quality(
    min_unique_genes = 5L,
    min_lib_size = 25L,
    min_cells = 5L
  ),
  streaming = 0L,
  .verbose = FALSE
)
dim(sc)
#> [1] 400  40

unlink(c(files, dir_data), recursive = TRUE, force = TRUE)