sc_toolbox.tools.generate_count_object#

sc_toolbox.tools.generate_count_object(adata, hue='disease', cell_type_label='cell_type', cell_type=None, min_samples=2, min_cells=5, ref='healthy', subset=None, layer='counts', outliers_removal=False)[source]#

@Meshal what is this really supposed to do?

Parameters:

  • adata – AnnData object

  • hue (str) – Value to color by

  • cell_type_label (str) – Label containing cell types

  • cell_type (Optional[List[str]]) – Cells type to generate counts for

  • min_samples (int) – Minimum samples for outlier removal with DBScan

  • min_cells (int) – Minimal number of cells

  • ref (str) –

  • subset (Optional[List[str]]) –

  • layer (str) –

  • outliers_removal (bool) – Whether to remove outliers or not

Returns:

AnnData object containing counts

Example Call: subset = [‘3d PI-KO’, ‘3d PI-WT’]

raw_counts = generate_count_object(adata,

condition = “grouping”, cell_type_label = “celltype_refined”, cell_type = [“AT2”], ref = “3d PI-WT”, subset = subset)