scanpy.read_loom¶
-
scanpy.read_loom(filename, sparse=True, cleanup=False, X_name='spliced', obs_names='CellID', var_names='Gene', 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.
- Parameters
- filename :
PathLikePathLike The filename.
- sparse :
boolbool(default:True) Whether to read the data matrix as sparse.
- cleanup :
boolbool(default:False) Whether to collapse all obs/var fields that only store one unique value into
.uns['loom-.'].- X_name :
strstr(default:'spliced') Loompy key with which the data matrix
.Xis initialized.- obs_names :
strstr(default:'CellID') Loompy key where the observation/cell names are stored.
- var_names :
strstr(default:'Gene') Loompy key where the variable/gene names are stored.
- **kwargs
Arguments to loompy.connect
- filename :
- Return type