torchcell.datasets.scerevisiae.dasilveira2014.MetaboliteDaSilveira2014Dataset
- class MetaboliteDaSilveira2014Dataset(root: str = 'data/torchcell/metabolite_dasilveira2014', io_workers: int = 0, transform: Any | None = None, pre_transform: Any | None = None, **kwargs: Any)[source]
Bases:
ExperimentDatasetMS lipidome of the yeast kinase/phosphatase deletion collection (127 mutants).
- 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 Table S4 lipid matrix + Table S10 ChEBI ids required before processing.
- process() None[source]
Parse the Quant sheet into per-mutant Metabolite experiments and write LMDB.
Every record is built and every refusal raised BEFORE
lipid_chebi.csv,data.csvor the store is written, so a refused matrix writes nothing underpreprocess/orprocessed/. Refusals (each 0 in the pinned Table S4, 2026.10.01: 147 lipids, 127 mutant rows): a lipid that no WT control row measured (it would have no reference value), two mutant rows naming one ORF, and a mutant row with every lipid blank. No row is refused or dropped for its gene name: each is stored under the names the release gives it.
- preprocess_raw(df: DataFrame, preprocess: dict[str, Any] | None = None) DataFrame[source]
Preprocessing is handled inside process() for this dataset.
- create_experiment(row: dict[str, Any]) tuple[MetaboliteExperiment, MetaboliteExperimentReference, Publication][source]
Build the Metabolite experiment/reference/publication for one mutant.