insitupy.InSituExperiment

class insitupy.InSituExperiment(data_type='insitupy')

A class to manage and analyze multiple spatially resolved single-cell transcriptomics experiments.

This class provides functionality for managing datasets, performing differential gene expression analysis, querying metadata, visualizing data, and saving/loading experiments. It operates on multiple datasets, each represented as an InSituData object, and maintains associated metadata in a pandas.DataFrame.

Supports two modes: 1. InSituPy mode (default): Stores InSituData objects 2. SpatialData mode: Stores StructuredSpatialData objects from SpatialData zarr stores

Examples

>>> # Create an InSituExperiment object
>>> experiment = InSituExperiment()

>>> # Add a dataset
>>> experiment.add(data="path/to/dataset", mode="insitupy", metadata={"experiment": "test"})

>>> # Read from SpatialData
>>> exp = InSituExperiment.read_spatialdata("path/to/data.zarr")

>>> # Perform differential gene expression analysis
>>> experiment.dge(target_id=0, ref_id=1, target_annotation_tuple=("cell_type", "neuron"))

>>> # Save the experiment
>>> experiment.saveas("path/to/save", overwrite=True)

>>> # Query the experiment
>>> subset = experiment.query({"experiment": ["test"]})

>>> # Plot UMAPs
>>> experiment.plot_umaps(color="cell_type", title_column="experiment")

__init__(data_type='insitupy')

Initialize an InSituExperiment object.

Parameters:

data_type (Literal['insitupy', 'spatialdata'] (default: 'insitupy')) – The type of data to store. Either “insitupy” (default) or “spatialdata”. Note: “spatialdata” mode is currently disabled and will be enabled in a future release.

Methods

__init__([data_type])	Initialize an InSituExperiment object.
add(data[, mode, metadata])	Add a dataset to the experiment and update metadata.
add_metadata_column(column_name, values[, ...])	Add a metadata column to the experiment.
append_metadata(new_metadata[, by, overwrite])	Append metadata to the existing InSituExperiment object.
calculate_qc_metrics([cells_layer, layer, ...])	Calculate quality control metrics for the InSituExperiment.
collect_anndatas(*args, **kwargs)
concat(objs[, new_col_name])	Concatenate multiple InSituExperiment objects.
copy()	Create a deep copy of the InSituExperiment object.
dge(target_id[, ref_id, ...])	Wrapper function for performing differential gene expression analysis within an InSituExperiment object.
from_config(config_path, mode[, ...])	Create an InSituExperiment object from a configuration file.
from_regions(data, region_key[, region_names])	Creates an InSituExperiment object from specified regions in the given InSituData.
get_n_cells([cells_layer])	Get the total number of cells across all datasets.
imetadata([fixed])	Displays the experiment-level metadata as an interactive table using itables.
import_from_anndata(adata, uid_column, ...)	Import observation and observation matrix data from an AnnData object into the experiment.
import_obs(*args, **kwargs)
iterdata()	Iterate over the metadata rows and corresponding data.
load_all([skip])	Load all data modalities for all datasets.
load_annotations()	Load annotations for all datasets.
load_cells()	Load cells for all datasets.
load_images([names, overwrite, verbose])	Load images for all datasets.
load_regions()	Load regions for all datasets.
load_transcripts([transcript_filename])	Load transcripts for all datasets.
plot_embedding(basis[, cells_layer, color, ...])	Create a plot with embeddings of all datasets as subplots.
plot_overview(*args, **kwargs)
plot_umaps([cells_layer, color, ...])	Create a plot with UMAPs of all datasets as subplots.
query(criteria)	Query the experiment based on metadata criteria.
read(path[, mode, filter_key])	Read an InSituExperiment object from a specified folder.
remove_history()	Remove history from all datasets.
remove_metadata_columns(columns)	Remove specified columns from the internal metadata.
save([verbose, collect_warnings_mode])	Save the full experiment to its existing project path.
save_colors([path, overwrite])	Save only experiment colors to colors.json.
save_filters([path])	Save only experiment filters to filters.json.
save_images([overwrite, collect_warnings_mode])	Save only image data for datasets in the experiment.
save_metadata([path, overwrite])	Save only experiment metadata to metadata.csv.
saveas(path[, overwrite, verbose, ...])	Save experiment to a new location (initial full write).
set_metadata_values(index, column_name, values)	Set metadata values for one or more indices.
show(index[, verbose])	Displays the dataset at the specified index.
show_modality(modality[, uid_column])	Show a modality for all datasets.
sync_colors(keys[, cells_layer, palette, ...])	Synchronize color dictionaries for categorical metadata across datasets.
to_anndata([cells_layer, label_col, ...])	Concatenate all datasets into a single AnnData object.

Attributes

annotations	Displays a summary of the 'annotations' modality for all datasets.
applied_filters
cells	Displays a summary of cells for all datasets.
colors	Color dictionaries created by sync_colors().
data	List of datasets as InSituData or StructuredSpatialData objects.
data_type	The type of data stored in this experiment ('insitupy' or 'spatialdata').
filter_masks	Raw filter dictionary mapping keys to boolean masks.
filters	Filter manager exposing filter operations (create, remove, clear, apply, view, rename).
images	Displays a summary of the 'images' modality for all datasets.
is_view
metadata	Returns the experiment-level metadata as a pandas DataFrame.
path	Save path of the InSituExperiment object.
regions	Displays a summary of the 'regions' modality for all datasets.
transcripts	Displays a summary of the 'transcripts' modality for all datasets.