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Load in h5ad with normalised counts to SingleCells

load_h5ad_norm.Rd

This function takes an h5ad file where only normalised counts are available in the X slot and loads the obs and var data into the DuckDB of the SingleCells class and the counts into a Rust-binarised format for rapid access. Raw counts are reconstructed from the normalised values using the library sizes stored in a specified obs column.

The reconstruction assumes the normalisation was: norm = log1p(x / lib_size * target_size)

Usage

load_h5ad_norm(
  object,
  h5_path,
  obs_lib_size_col,
  target_size,
  sc_qc_param = params_sc_min_quality(),
  streaming = TRUE,
  cell_id_col = NULL,
  batch_size = 1000L,
  .verbose = TRUE
)

Arguments

object

SingleCells class.

h5_path

File path to the h5ad object you wish to load in.

obs_lib_size_col

String. Name of the obs column containing the total counts per cell or spot (e.g. "nCount_RNA"). You will have to check the original obs data for this.

target_size

Numeric. The target size used in the original normalisation (e.g. 1e4).

sc_qc_param

List. Output of params_sc_min_quality(). A list with the following elements:

  • min_unique_genes - Integer. Minimum number of genes to be detected in the cell to be included.

  • min_lib_size - Integer. Minimum library size in the cell to be included.

  • min_cells - Integer. Minimum number of cells a gene needs to be detected to be included.

  • target_size - Float. Target size to normalise to. Defaults to 1e5.

streaming

Boolean. Shall the data be streamed during the conversion of CSR to CSC. Defaults to TRUE and should be used for larger data sets.

cell_id_col

Optional string. If a specific column in the h5ad obs data represents the cell identifiers, you can specify it here.

batch_size

Integer. If streaming = TRUE, how many cells to process in one batch. Defaults to 1000L.

.verbose

Boolean. Controls the verbosity of the function.

Value

It will populate the files on disk and return the class with updated shape information.