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Improve neighbors_key docstring for make_nhoods #940

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Zethson merged 1 commit into from
Mar 24, 2026
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Improve neighbors_key docstring for make_nhoods #940

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8 changes: 5 additions & 3 deletions pertpy/tools/_milo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -73,8 +73,8 @@ def make_nhoods(
Args:
data: AnnData object with KNN graph defined in `obsp` or MuData object with a modality with KNN graph defined in `obsp`
neighbors_key: The key in `adata.obsp` or `mdata[feature_key].obsp` to use as KNN graph.
If not specified, `make_nhoods` looks .obsp[‘connectivities’] for connectivities (default storage places for `scanpy.pp.neighbors`).
If specified, it looks at .obsp[.uns[neighbors_key][‘connectivities_key’]] for connectivities.
If not specified, `make_nhoods` looks at `.obsp['connectivities']` for connectivities.
If specified, looks at `.obsp[neighbors_key + '_connectivities']` for connectivities.
feature_key: If input data is MuData, specify key to cell-level AnnData object.
prop: Fraction of cells to sample for neighbourhood index search.
seed: Random seed for cell sampling.
Expand Down Expand Up @@ -540,7 +540,9 @@ def annotate_nhoods(
sample_adata.var["nhood_annotation_frac"] = anno_frac_dataframe.max(axis=1)

def annotate_nhoods_continuous(self, mdata: MuData, anno_col: str, feature_key: str | None = "rna"):
"""Assigns a continuous value to neighbourhoods, based on mean cell level covariate stored in adata.obs. This can be useful to correlate DA log-foldChanges with continuous covariates such as pseudotime, gene expression scores etc...
"""Assigns a continuous value to neighbourhoods, based on mean cell level covariate stored in adata.obs.

This can be useful to correlate DA log-foldChanges with continuous covariates such as pseudotime, gene expression scores etc...

Args:
mdata: MuData object
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