liana.multi.adata_to_views

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liana.multi.adata_to_views#

liana.multi.adata_to_views(adata, groupby, sample_key, obs_keys=None, view_sep=':', keep_stats=False, verbose=False, psbulk_kwargs=None, filter_samples_kwargs=None, filter_by_expr_kwargs=None, filter_by_prop_kwargs=None)#

Converts an AnnData object to a MuData object with views that represent an aggregate for each entity in adata.obs[groupby].

Parameters:

  • adata (AnnData) – Annotated data object.

  • groupby (str) – Key to be used for grouping.

  • sample_key (str) – key in adata.obs to use for grouping by sample or context.

  • obs_keys (list[str] (default: None)) – Column names in adata.obs to merge with the MuData object

  • view_sep (str (default: ':')) – Separator to use when assigning adata.var_names to views

  • keep_stats (bool (default: False)) – If True, keep the pseudobulk statistics in mdata.uns['psbulk_stats']. Default is False.

  • verbose (bool (default: False)) – Verbosity flag.

  • psbulk_kwargs (dict (default: None)) – Arguments to pass to dc.pp.pseudobulk for pseudobulking. See decoupler documentation for more details.

  • filter_samples_kwargs (dict (default: None)) – Arguments to pass to dc.pp.filter_samples for filtering samples. See decoupler documentation for more details. If None, won’t filter.

  • filter_by_expr_kwargs (dict (default: None)) – Optional mapping of arguments to pass to dc.pp.filter_by_expr for gene filtering by expression. If None, won’t filter.

  • filter_by_prop_kwargs (dict (default: None)) – Optional mapping of arguments to pass to dc.pp.filter_by_prop for gene filtering by proportion of cells that express the gene. If None, won’t filter.

Return type:

MuData

Returns:

Returns a MuData object with views that represent an aggregate for each entity in adata.obs[groupby].

Examples

Each cell type becomes a view of pseudobulk profiles, with samples as the observations – the multicellular structure that MOFA is then fit on:

>>> import liana as li
>>> adata = li.testing.generate_toy_adata()
>>> mdata = li.mu.adata_to_views(adata,
...                              groupby='bulk_labels',
...                              sample_key='sample',
...                              obs_keys=['case'],
...                              psbulk_kwargs={'raw': True, 'skip_checks': True})

Only the views that survive the expression filters are kept, each variable is prefixed with its view, and obs_keys are joined onto the sample-level .obs. Pass filter_by_expr_kwargs to tighten or relax those filters – they go straight to decoupler.

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