scanpy.read_loom¶
-
scanpy.
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.
- Parameters
- filename :
PathLike
PathLike
The filename.
- sparse :
bool
bool
(default:True
) Whether to read the data matrix as sparse.
- cleanup :
bool
bool
(default:False
) Whether to collapse all obs/var fields that only store one unique value into
.uns['loom-.']
.- X_name :
str
str
(default:'spliced'
) Loompy key with which the data matrix
X
is initialized.- obs_names :
str
str
(default:'CellID'
) Loompy key where the observation/cell names are stored.
- obsm_names :
Mapping
,None
Optional
[Mapping
[str
,Iterable
[str
]]] (default:None
) Loompy keys which will be constructed into observation matrices
- var_names :
str
str
(default:'Gene'
) 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
- filename :
- Return type