scpanel.select_cell

Functions

`split_patients`(→ Tuple[anndata._core.anndata.AnnData, ...)
`cal_bootstrap_score`(→ pandas.core.frame.DataFrame)
`custom_metrics`(→ Dict[str, numpy.float64])
`cell_type_score`(→ Tuple[pandas.core.frame.DataFrame, ...)
`plot_cell_type_score`(→ matplotlib.axes._axes.Axes)
`select_celltype`(→ anndata._core.anndata.AnnData)

scpanel.select_cell.split_patients(adata: anndata._core.anndata.AnnData, test_pt_size: float, random_state: int, out_dir: str, verbose: bool) → Tuple[anndata._core.anndata.AnnData, anndata._core.anndata.AnnData]

scpanel.select_cell.cal_bootstrap_score(adata: anndata._core.anndata.AnnData, out_dir: str, sample_n_cell: int, n_iterations: int = 100, n_threads: int = 16, show_progress: bool = True, verbose: bool = False) → pandas.core.frame.DataFrame

scpanel.select_cell.custom_metrics(grouping: Tuple[str, pandas.core.frame.DataFrame], metric: str) → Dict[str, numpy.float64]

scpanel.select_cell.cell_type_score(adata_train_dict: Dict[str, anndata._core.anndata.AnnData], out_dir: str, ncpus: int, sample_n_cell: int, n_iterations: int = 100, verbose: bool = False) → Tuple[pandas.core.frame.DataFrame, pandas.core.frame.DataFrame]

scpanel.select_cell.plot_cell_type_score(AUC: pandas.core.frame.DataFrame, AUC_all: pandas.core.frame.DataFrame, width: int = 4, height: int = 5) → matplotlib.axes._axes.Axes

scpanel.select_cell.select_celltype(adata_train_dict: Dict[str, anndata._core.anndata.AnnData], out_dir: str, celltype_selected: str) → anndata._core.anndata.AnnData