spamosaic.build_graph.remove_outlier

spamosaic.build_graph.remove_outlier(mnn_set, ad1, ad2, contamination='auto')[source]

Remove outlier cell pairs from an MNN set based on spatial distance patterns.

This function uses an Isolation Forest model to detect and remove spatial outlier cell pairs from a set of mutual nearest neighbors (MNNs). It constructs a feature matrix based on spatial coordinates from both datasets and their differences, then filters out pairs classified as outliers.

Parameters:

  • mnn_set (set of tuple[str, str]) – Set of MNN cell pairs represented by (cell_id_1, cell_id_2).

  • ad1 (AnnData) – First AnnData object containing ‘spatial’ in .obsm.

  • ad2 (AnnData) – Second AnnData object containing ‘spatial’ in .obsm.

  • contamination (str or float, default='auto') – The amount of contamination (i.e., expected proportion of outliers) used to define the threshold in the Isolation Forest. Follows scikit-learn’s format.

Returns:

Filtered MNN set with spatial outliers removed.

Return type:

set of tuple[str, str]