omicverse.single.DCT

Contents

omicverse.single.DCT#

class omicverse.single.DCT(adata, condition, ctrl_group, test_group, cell_type_key, method='sccoda', sample_key=None, use_rep=None)[source]#

Differential cell-type abundance testing wrapper.

Parameters:

  • adata (AnnData) – Input single-cell AnnData.

  • condition (str) – Condition column in adata.obs.

  • ctrl_group (str) – Control-group label.

  • test_group (str) – Test-group label.

  • cell_type_key (str) – Cell-type annotation column.

  • method (str, default='sccoda') – Differential-abundance backend.

__init__(adata, condition, ctrl_group, test_group, cell_type_key, method='sccoda', sample_key=None, use_rep=None)[source]#

Initialize differential cell-type abundance analysis.

Parameters:

  • adata (AnnData) – Single-cell AnnData object.

  • condition (str) – Obs column containing condition labels.

  • ctrl_group (str) – Control condition label.

  • test_group (str) – Test condition label.

  • cell_type_key (str) – Obs column containing cell-type annotations.

  • method (str, default='sccoda') – Differential abundance method: 'sccoda', 'milo', or 'milopy'.

  • sample_key (str or None, default=None) – Obs column containing sample IDs (required for Milo methods).

  • use_rep (str or None, default=None) – Embedding key in adata.obsm used for neighborhood graph in Milo.

Return type:

None

Methods

__init__(adata, condition, ctrl_group, ...)

Initialize differential cell-type abundance analysis.

get_results([mix_threshold])

Retrieve differential abundance results.

run(**kwargs)

Run differential abundance testing.
Contents