read_loom

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) {
ad <- read_loom("dataset.loom")
}