snapatac2.tl.marker_regions#

snapatac2.tl.marker_regions(data, groupby, pvalue=0.01)[source]#

Select marker regions for each group by z-score enrichment.

Use this lightweight screen to obtain candidate group-specific regions from aggregated accessibility before running more formal differential tests.

Anti-Patterns#

  • Do NOT treat these markers as regression-adjusted differential results; use diff_test for hypothesis testing between two cell groups.

  • Do NOT pass a grouping key that is absent from data.obs.

param data:

Annotated data object with regions in .var_names and counts in .X.

type data:

AnnData | AnnDataSet

param groupby:

Grouping key in data.obs, or one group label per cell.

type groupby:

str | list[str]

param pvalue:

One-sided normal survival-function threshold applied to z-scores.

type pvalue:

float

returns:

Mapping from group name to marker region names.

rtype:

dict[str, list[str]]

Examples

>>> import snapatac2 as snap
>>> adata = snap.datasets.pbmc5k(type="annotated_h5ad")
>>> markers = snap.tl.marker_regions(adata, groupby="cell_type", pvalue=0.01)
>>> isinstance(markers, dict)
True
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