tiledbsoma.Experiment

class tiledbsoma.Experiment(handle: GroupWrapper, **kwargs: Any)

A collection subtype that combines observations and measurements from an individual experiment.

In single cell biology, this can represent multiple modes of measurement across a single collection of cells (i.e., a “multimodal dataset”). Within an experiment, a set of measurements on a single set of variables (i.e., features) is represented as a Measurement.

obs

Primary annotations on the observation axis. The contents of the soma_joinid column define the observation index domain, AKA obs_id. All observations for the Experiment must be defined in this dataframe.

Type:

DataFrame

ms

A collection of named measurements.

Type:

Collection

Example

>>> import tiledbsoma
>>> with tiledbsoma.open("/path/to/experiment") as exp:
...     # While users can interact directly with an Experiment's fields:
...     obs_df = exp.obs
...
...     # the primary use case is to run queries on the experiment data.
...     q = exp.query(
...         "mtdna",
...         obs_query=tiledbsoma.AxisQuery(value_filter="tissue == 'lung'"),
...         var_query=tiledbsoma.AxisQuery(coords=(slice(50, 100),)),
...     )
...     query_obs = q.obs().concat().to_pandas()
...     query_var = q.var().concat().to_pandas()

Lifecycle

Experimental.

__init__(handle: GroupWrapper, **kwargs: Any)

Internal-only common initializer steps.

This function is internal; users should open TileDB SOMA objects using the create() and open() factory class methods.

Methods

__init__(handle, **kwargs)	Internal-only common initializer steps.
add_new_collection(key[, kind, uri, ...])	Adds a new sub-collection to this collection.
add_new_dataframe(key, *[, uri, ...])	Adds a new DataFrame to this collection.
add_new_dense_ndarray(key, *, cls[, uri, ...])	Adds a new DenseNDArray to this Collection.
add_new_sparse_ndarray(key, *, cls[, uri, ...])	Adds a new SparseNDArray to this Collection.
axis_query(measurement_name, *[, obs_query, ...])	Creates an axis query over this experiment.
clear()
close()	Release any resources held while the object is open.
create(uri, *[, platform_config, context, ...])	Creates and opens a new SOMA collection in storage.
exists(uri[, context, tiledb_timestamp])	Finds whether an object of this type exists at the given URI.
get(k[,d])
items()
keys()
open(uri[, mode, tiledb_timestamp, context, ...])	Opens this specific type of SOMA object.
pop(k[,d])	If key is not found, d is returned if given, otherwise KeyError is raised.
popitem()	as a 2-tuple; but raise KeyError if D is empty.
set(key, value, *[, use_relative_uri])	Adds an element to the collection.
setdefault(k[,d])
update([E, ]**F)	If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
values()
verify_open_for_writing()	Raises an error if the object is not open for writing.

Attributes

closed	True if the object has been closed.
context	A value storing implementation-specific configuration information.
metadata	The metadata of this SOMA object.
mode	The mode this object was opened in, either r or w.
ms	A collection of named measurements.
obs	Primary observations on the observation axis.
soma_type	A string describing the SOMA type of this object.
tiledb_timestamp	The time that this object was opened in UTC.
tiledb_timestamp_ms	The time this object was opened, as millis since the Unix epoch.
uri	Accessor for the object's storage URI.