INNER CODE UNIT · Python

cooks_cutoff

scverse/PyDESeq2 · src/pydeseq2/dds.py:1033

        cooks_cutoff = f.ppf(0.99, num_vars, num_samples - num_vars)

        # As in DESeq2, only take samples with 3 or more replicates when looking for
        # max cooks.
        use_for_max = n_or_more_replicates(self.obsm["design_matrix"], 3)

        # If for a gene there are 3 samples or more that have more counts than the
        # maximum cooks sample, don't count this gene as an outlier.

        # Take into account whether we already replaced outliers
        if (
            self.refit_cooks
            and (self.var["refitted"].sum() > 0)
            and "replace_cooks" in self.layers.keys()
        ):
            cooks_outlier = (
                self.layers["replace_cooks"][use_for_max, :] > cooks_cutoff
            ).any(axis=0)

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