liana.multi.lrs_to_views#
- liana.multi.lrs_to_views(adata, score_key=None, inverse_fun=<function DefaultValues.inverse_fun>, obs_keys=None, lr_prop=0.5, lr_fill=nan, lrs_per_view=20, lrs_per_sample=10, samples_per_view=3, min_variance=0, min_var_nbatches=1, batch_key=None, lr_sep='^', cell_sep='&', var_sep=':', uns_key='liana_res', sample_key='sample', source_key='source', target_key='target', ligand_key='ligand_complex', receptor_key='receptor_complex', verbose=False)#
Converts a LIANA result to a MuData object with views that represent an aggregate for each entity in
adata.obs[groupby].- Parameters:
adata (
AnnData) – Annotated data object.score_key (
str|None(default:None)) – Column name of the score inliana_res. If None, the score is inferred from the method.inverse_fun (
Callable(default:<function DefaultValues.inverse_fun at 0x70889f57c680>)) – Function that is applied to the scores before building the views. Default islambda x: 1 - xwhich 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|None(default:None)) – List of keys inadata.obsthat should be included in the MuData object. These columns should correspond to the number of samples inadata.obs[sample_key].lr_prop (
float(default:0.5)) – Reflects the minimum required proportion of samples for an interaction to be considered for building the views.lr_fill (
float(default:nan)) – Value to fill in for interactions that are not present in a view. Default isnp.nan.lrs_per_view (
int(default:20)) – Reflects the minimum required number of interactions in a view to be considered for building the views.lrs_per_sample (
int(default:10)) – Reflects the minimum required number of interactions in a sample to be considered when building a specific view.samples_per_view (
int(default:3)) – Reflects the minimum required samples to keep a view.min_variance (
int(default:0)) – Reflects the minimum required variance across samples for each interaction in each view. NaNs are ignored when computing the variance.min_var_nbatches (
int(default:1)) – Reflect the minimum number of batches (>=) that must have a variance abovemin_variancefor an interaction to be included in the view.batch_key (
str(default:None)) – Key inadata.obsthat represents the batch information. Used solely when computing the variance. If batch_key is notNone, the variance is computed per batch, and the ``lr_sep (
str(default:'^')) – Separator to use when joining ligand and receptor names into interactions.cell_sep (
str(default:'&')) – Separator to use for the cell names in the views.var_sep (
str(default:':')) – Separator to use for the variable names in the views.uns_key (
str(default:'liana_res')) – Key inadata.unsthat contains the LIANA results. Default is'liana_res'.sample_key (
str(default:'sample')) – key inadata.obsto use for grouping by sample or context.source_key (
str(default:'source')) – Column name of the sender/source cell types inliana_res.target_key (
str(default:'target')) – Column name of the receiver/target cell types inliana_res.ligand_key (
str(default:'ligand_complex')) – Column name of the ligand inliana_res.receptor_key (
str(default:'receptor_complex')) – Column name of the receptor inliana_res.verbose (
bool(default:False)) – Verbosity flag.
- Return type:
MuData- Returns:
Returns a MuData object with views that represent an aggregate for each entity in
adata.obs[groupby].- Raises:
ValueError – If any of the provided keys are not found in the corresponding
adataview.