- dynamo.read_loom(filename, sparse=True, cleanup=False, X_name='spliced', obs_names='CellID', obsm_names=None, var_names='Gene', varm_names=None, dtype='float32', **kwargs)
Read .loom-formatted hdf5 file.
This reads the whole file into memory.
Beware that you have to explicitly state when you want to read the file as sparse data.
PathLike) – The filename.
bool) – Whether to read the data matrix as sparse.
bool) – Whether to collapse all obs/var fields that only store one unique value into .uns[‘loom-.’].
str) – Loompy key where the observation/cell names are stored.
str) – Loompy key where the variable/gene names are stored.
obsm_names – Loompy keys which will be constructed into variable matrices
**kwargs – Arguments to loompy.connect
- Return type