scanpy.read

scanpy.read(filename, backed=None, sheet=None, ext=None, delimiter=None, first_column_names=False, backup_url=None, cache=False, cache_compression=None, **kwargs)

Read file and return AnnData object.

To speed up reading, consider passing cache=True, which creates an hdf5 cache file.

Parameters
filename : Path, strUnion[Path, str]

If the filename has no file extension, it is interpreted as a key for generating a filename via sc.settings.writedir / (filename + sc.settings.file_format_data). This is the same behavior as in sc.read(filename, ...).

backed : {None, 'r', 'r+'}

If 'r', load AnnData in backed mode instead of fully loading it into memory (memory mode). If you want to modify backed attributes of the AnnData object, you need to choose 'r+'.

sheet : str, NoneOptional[str] (default: None)

Name of sheet/table in hdf5 or Excel file.

ext : str, NoneOptional[str] (default: None)

Extension that indicates the file type. If None, uses extension of filename.

delimiter : str, NoneOptional[str] (default: None)

Delimiter that separates data within text file. If None, will split at arbitrary number of white spaces, which is different from enforcing splitting at any single white space ' '.

first_column_names : boolbool (default: False)

Assume the first column stores row names. This is only necessary if these are not strings: strings in the first column are automatically assumed to be row names.

backup_url : str, NoneOptional[str] (default: None)

Retrieve the file from an URL if not present on disk.

cache : boolbool (default: False)

If False, read from source, if True, read from fast ‘h5ad’ cache.

cache_compression : {'gzip', 'lzf', None}

See the h5py Filter pipeline.

kwargs

Parameters passed to read_loom().

Return type

AnnDataAnnData

Returns

An AnnData object