BAITS.VDJ.tl.calculate_qc_umis

BAITS.VDJ.tl.calculate_qc_umis#

BAITS.VDJ.tl.calculate_qc_umis(df, group_by, Cgene_col, clone_col, loc_x_col='X', loc_y_col='Y', plot=True, figsize=(7, 3.5))#

Compute per-group and per-spatial-location UMI counts for clones.

Parameters:

  • df (pandas.DataFrame) – Input dataframe containing clone, chain, and spatial information.

  • group_by (str) – Column name to group by (e.g., sample or tissue region).

  • Cgene_col (str) – Column name for chain (Cgene).

  • clone_col (str) – Column containing clone identifiers.

  • loc_x_col (str, default='X') – Column name for x-coordinate.

  • loc_y_col (str, default='Y') – Column name for y-coordinate.

  • plot (bool, default=True) – Whether to generate QC boxplots.

  • figsize (tuple, default=(7,3.5)) – Figure size for plots.

Returns:

Original dataframe with additional columns: - ‘umis_by_group’: total UMIs per group - ‘umis_by_group_spatialLoc’: total UMIs per spatial location

Return type:

pandas.DataFrame

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