read_loom {anndata} | R Documentation |
read_loom
Description
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 |
X_name |
Loompy key with which the data matrix |
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
## Not run:
ad <- read_loom("dataset.loom")
## End(Not run)
[Package anndata version 0.7.5.6 Index]