bioneuralnet.datasets¶

Built-in datasets for BioNeuralNet.

This module provides specific loader functions for each available multi-omics dataset.

Functions

`load_brca`()	Load the Breast Invasive Carcinoma (BRCA) dataset.
`load_example`()	Load the synthetic Example dataset.
`load_kipan`()	Load the Pan-kidney (KIPAN) dataset.
`load_lgg`()	Load the Brain Lower Grade Glioma dataset.
`load_monet`()	Load the synthetic MONET dataset.

Classes

DatasetLoader(dataset_name)

Load a pre-packaged multi-omics dataset from the package.

class bioneuralnet.datasets.DatasetLoader(dataset_name: str)[source]¶

Bases: object

Load a pre-packaged multi-omics dataset from the package.

Options for ‘dataset_name’:

“example”: Synthetic example. “monet”: Synthetic example. “brca”: Breast invasive carcinoma. “lgg”: Brain Lower Grade Glioma. “kipan”: Pan-kidney carcinoma.

Parameters:

dataset_name (str) – Normalized dataset name.
base_dir (Path) – Directory where the dataset folders live.
data (dict[str, pd.DataFrame]) – Mapping from table name to loaded DataFrame.

property shape: dict[str, tuple[int, int]]¶: Dictionary mapping each table name to its (n_rows, n_cols) shape.

bioneuralnet.datasets.load_brca() → dict[source]¶

Load the Breast Invasive Carcinoma (BRCA) dataset.

Returns:: Keys include ‘mirna’, ‘target’, ‘clinical’, ‘rna’, ‘methylation’.
Return type:: dict

bioneuralnet.datasets.load_example() → dict[source]¶

Load the synthetic Example dataset.

Returns:: Keys include ‘X1’, ‘X2’, ‘Y’, ‘clinical’.
Return type:: dict

bioneuralnet.datasets.load_kipan() → dict[source]¶

Load the Pan-kidney (KIPAN) dataset.

Returns:: Keys include ‘mirna’, ‘target’, ‘clinical’, ‘rna’, ‘methylation’.
Return type:: dict

bioneuralnet.datasets.load_lgg() → dict[source]¶

Load the Brain Lower Grade Glioma dataset.

Returns:: Keys include ‘mirna’, ‘target’, ‘clinical’, ‘rna’, ‘methylation’.
Return type:: dict

bioneuralnet.datasets.load_monet() → dict[source]¶

Load the synthetic MONET dataset.

Returns:: Keys include ‘gene’, ‘mirna’, ‘phenotype’, ‘rppa’, ‘clinical’.
Return type:: dict

Modules

dataset_loader