torchcell.datasets.scerevisiae.cachera2023.BetaxanthinCachera2023Dataset

class BetaxanthinCachera2023Dataset(root: str = 'data/torchcell/betaxanthin_cachera2023', io_workers: int = 0, transform: Callable[[...], Any] | None = None, pre_transform: Callable[[...], Any] | None = None, **kwargs: Any)

Bases: ExperimentDataset

Genome-wide betaxanthin CRI-SPA product-proxy screen of the YKO collection.

organism: ClassVar[Organism] = 'scerevisiae'

each loader declares its own, the build’s organism switch reads it off the class (dataset_organism), and a loader that forgot it is refused by name instead of inheriting an organism it may not have.

Type:

The host organism every record describes. Annotated here WITHOUT a value

property experiment_class: type[Experiment]

Experiment schema class produced by this dataset.

property reference_class: type[ExperimentReference]

Experiment-reference schema class produced by this dataset.

property raw_file_names: list[str]

The gene-level CRI-SPA dataset required before processing.

download() → None

Download the gene-level CRI-SPA dataset from the authors’ GitHub repo.

The stored artifact’s sha256 is canonical: a freshly downloaded payload is verified before it is written, and the file in raw/ (present or fresh) is verified against DATA_SHA256 at the start of process. A mismatch means upstream drift or corruption and raises (never silently followed).

process() → None

Store every released deletion row as a Metabolite experiment; write LMDB.

preprocess_raw(df: DataFrame, preprocess: dict[str, Any] | None = None) → DataFrame

Preprocessing is handled inside process() for this dataset.

create_experiment(row: dict[str, Any]) → tuple[MetaboliteExperiment, MetaboliteExperimentReference, Publication]

Build the Metabolite experiment/reference/publication for one released row.