czbenchmarks.datasets.single_cell

Attributes

logger

Classes

SingleCellDataset

Single cell dataset containing gene expression data and metadata.

PerturbationSingleCellDataset

Single cell dataset with perturbation data, containing control and

Module Contents

czbenchmarks.datasets.single_cell.logger
class czbenchmarks.datasets.single_cell.SingleCellDataset(path: str, organism: czbenchmarks.datasets.types.Organism)[source]

Bases: czbenchmarks.datasets.base.BaseDataset

Single cell dataset containing gene expression data and metadata.

Handles loading and validation of AnnData objects with gene expression data and associated metadata for a specific organism.

load_data() None[source]

Load the dataset into memory.

This method should be implemented by subclasses to load their specific data format. For example, SingleCellDataset loads an AnnData object from an h5ad file.

The loaded data should be stored as instance attributes that can be accessed by other methods.

unload_data() None[source]

Unload the dataset from memory.

This method should be implemented by subclasses to free memory by clearing loaded data. For example, SingleCellDataset sets its AnnData object to None.

This is used to clear memory-intensive data before serialization, since serializing large raw data artifacts can be error-prone and inefficient.

Any instance attributes containing loaded data should be cleared or set to None.

property organism: czbenchmarks.datasets.types.Organism
property adata: anndata.AnnData
class czbenchmarks.datasets.single_cell.PerturbationSingleCellDataset(path: str, organism: czbenchmarks.datasets.types.Organism, condition_key: str = 'condition', split_key: str = 'split')[source]

Bases: SingleCellDataset

Single cell dataset with perturbation data, containing control and perturbed cells.

Input data requirements:

  • H5AD file containing single cell gene expression data

  • Must have a condition column in adata.obs specifying control (“ctrl”) and perturbed conditions.

  • Must have a split column in adata.obs to identify test samples

  • Condition format must be one of:

    • ctrl for control samples

    • {gene}+ctrl for single gene perturbations

    • {gene1}+{gene2} for combinatorial perturbations

load_data() None[source]

Load the dataset into memory.

This method should be implemented by subclasses to load their specific data format. For example, SingleCellDataset loads an AnnData object from an h5ad file.

The loaded data should be stored as instance attributes that can be accessed by other methods.

unload_data() None[source]

Unload the dataset from memory.

This method should be implemented by subclasses to free memory by clearing loaded data. For example, SingleCellDataset sets its AnnData object to None.

This is used to clear memory-intensive data before serialization, since serializing large raw data artifacts can be error-prone and inefficient.

Any instance attributes containing loaded data should be cleared or set to None.

property perturbation_truth: Dict[str, pandas.DataFrame]
property condition_key: str
property split_key: str