mantispy.pp.calculate_qc_metrics#

mantispy.pp.calculate_qc_metrics(adata, image_shape=None, border_margin=10, max_nan_fraction=0.5, copy=False)[source]#

Compute per-cell and per-feature QC metrics.

Parameters:
adata AnnData

Object to annotate.

image_shape tuple[int, int] | None (default: None)

(height, width) of a field of view. Without it, and without Metadata_Center_X/_Y in obs, the border flag stays False.

border_margin int (default: 10)

Distance from the image edge, in pixels, inside which a cell is a border cell.

max_nan_fraction float (default: 0.5)

Largest fraction of missing features a cell may have and still pass. Partial NaN is routine in CellProfiler output (Zernike and RadialDistribution features are undefined for small objects), so requiring no missing values would fail almost every cell.

copy bool (default: False)

Return a modified copy instead of mutating in place.

Return type:

AnnData | None

Returns:

None, or the modified copy. Writes the obs columns qc_n_nan_features, qc_nan_fraction, qc_is_border, qc_area_outlier and qc_pass, and the var columns qc_n_nan, qc_variance and qc_n_unique.

Raises:

KeyError – If no column in var names an area, so qc_area_outlier cannot be scored and qc_pass would be an and over one check fewer than it claims.