liana.multi.lrs_to_views

liana.multi.lrs_to_views(adata: AnnData, score_key: str or None = None, inverse_fun: callable = <function DefaultValues.inverse_fun>, obs_keys: list or None = None, lr_prop: float = 0.5, lr_fill: np.nan = nan, lrs_per_view: int = 20, lrs_per_sample: int = 10, samples_per_view: int = 3, min_variance: int = 0, min_var_nbatches=1, batch_key=None, lr_sep: str = '^', cell_sep: str = '&', var_sep: str = ':', uns_key: str = 'liana_res', sample_key: str = 'sample', source_key: str = 'source', target_key: str = 'target', ligand_key: str = 'ligand_complex', receptor_key: str = 'receptor_complex', verbose: bool = False)

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

Parameters:

adata

Annotated data object.

score_key

Column name of the score in liana_res. If None, the score is inferred from the method.

inverse_fun

Function that is applied to the scores before building the views. Default is lambda x: 1 - x which is used to invert the scores reflect probabilities (e.g. magnitude_rank), i.e. such for which lower values reflect higher relevance. This is handled automatically for the scores in liana.

obs_keys

List of keys in adata.obs that should be included in the MuData object. These columns should correspond to the number of samples in adata.obs[sample_key].

lr_prop

Reflects the minimum required proportion of samples for an interaction to be considered for building the views.

lr_fill

Value to fill in for interactions that are not present in a view. Default is np.nan.

lrs_per_sample

Reflects the minimum required number of interactions in a sample to be considered when building a specific view.

lrs_per_view

Reflects the minimum required number of interactions in a view to be considered for building the views.

samples_per_view

Reflects the minimum required samples to keep a view.

min_variance

Reflects the minimum required variance across samples for each interaction in each view. NaNs are ignored when computing the variance.

batch_key

Key in adata.obs that represents the batch information. Used solely when computing the variance. If batch_key is not None, the variance is computed per batch, and the ``

min_var_nbatches

Reflect the minimum number of batches (>=) that must have a variance above min_variance for an interaction to be included in the view.

lr_sep

Separator to use when joining ligand and receptor names into interactions.

cell_sep

Separator to use for the cell names in the views.

var_sep

Separator to use for the variable names in the views.

uns_key

Key in adata.uns that contains the LIANA results. Default is ‘liana_res’.

sample_key

key in adata.obs to use for grouping by sample or context.

source_key

Column name of the sender/source cell types in liana_res.

target_key

Column name of the receiver/target cell types in liana_res.

ligand_key

Column name of the ligand in liana_res.

receptor_key

Column name of the receptor in liana_res.

verbose

Verbosity flag.

Returns:

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