read_loom — read_loom • anndata

Read .loom-formatted hdf5 file.

Usage

read_loom(
  filename,
  sparse = TRUE,
  cleanup = FALSE,
  X_name = "spliced",
  obs_names = "CellID",
  obsm_names = NULL,
  var_names = "Gene",
  varm_names = NULL,
  dtype = "float32",
  ...
)

Arguments

filename: The filename.
sparse: Whether to read the data matrix as sparse.
cleanup: Whether to collapse all obs/var fields that only store one unique value into .uns['loom-.'].
X_name: Loompy key with which the data matrix AnnData.X is initialized.
obs_names: Loompy key where the observation/cell names are stored.
obsm_names: Loompy keys which will be constructed into observation matrices
var_names: Loompy key where the variable/gene names are stored.
varm_names: Loompy keys which will be constructed into variable matrices
dtype: Numpy data type.
...: Arguments to loompy.connect

Details

This reads the whole file into memory. Beware that you have to explicitly state when you want to read the file as sparse data.

Examples

if (FALSE) { # \dontrun{
ad <- read_loom("dataset.loom")
} # }