mantispy.pp.outliers

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mantispy.pp.outliers#

mantispy.pp.outliers(adata, method='ecod', contamination=0.01, score_cutoff=None, key='selected', by=None, seed=0, ecod_aggregation='pyod', key_added='qc_outlier', copy=False)#

Flag outlying cells.

Every method produces a score where higher means more outlying, and the same thresholding applies to all of them, so contamination is the flagged fraction whichever method is used.

Parameters:

  • adata (AnnData) – Object to flag.

  • method (str (default: 'ecod')) – "ecod" [Li et al., 2023] needs no tuning and is interpretable per feature, "isolation_forest" catches outliers defined by feature interactions, and "mad" takes the largest robust z-score across features, which is easy to explain but sees each feature alone.

  • contamination (float (default: 0.01)) – Fraction of cells to flag, rounded up to a whole cell within each by group, so a non-empty group always flags its most outlying cell and the flagged fraction is higher than asked for in a group smaller than 1 / contamination. Ignored when score_cutoff is given.

  • score_cutoff (float | None (default: None)) – Threshold the score absolutely instead of by quantile. With method="mad" the score is a robust z-score, so score_cutoff=5 gives the usual rule.

  • key (str | None (default: 'selected')) – Restrict to features flagged by this boolean var column, usually "selected". Falls back to every feature when the column is absent.

  • by (str | None (default: None)) – Threshold within each group of this obs column, e.g. per plate, rather than globally.

  • seed (int (default: 0)) – Seed for isolation_forest.

  • ecod_aggregation (str (default: 'pyod')) – How "ecod" combines features. "pyod" sums each feature’s larger tail, or both tails where its skewness is zero or undefined, as pyod and scmorph do, so no score depends on which way round a feature is measured. "paper" is Algorithm 1 of Li et al. [2023], the largest of the left-tail, right-tail and skew-directed sums.

  • key_added (str (default: 'qc_outlier')) – Prefix for the outputs: obs[key_added] and obs[key_added + "_score"].

  • 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 boolean obs[key_added] and the score itself to obs[key_added + "_score"].

Raises:

ValueError – If method or ecod_aggregation is unknown, or contamination is outside (0, 1) and no score_cutoff is given.

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