liana.mt.connectome.__call__#
- connectome.__call__(adata, groupby, resource_name='consensus', expr_prop=0.1, min_cells=5, groupby_pairs=None, base=np.float64(2.718281828459045), supp_columns=None, return_all_lrs=False, key_added='liana_res', use_raw=False, layer=None, de_method='t-test', n_perms=1000, seed=1337, n_jobs=1, resource=None, interactions=None, spatial_key=None, spatial_kwargs=None, mdata_kwargs=None, inplace=True, verbose=False)#
Run a ligand-receptor method.
- Parameters:
- adata
AnnData|MuData Annotated data object.
- groupby
str Key to be used for grouping.
- resource_name
str(default:'consensus') Name of the resource to be used for ligand-receptor inference. See
li.rs.show_resources()for available resources.- expr_prop
float(default:0.1) Minimum expression proportion for the ligands and receptors (+ their subunits) in the corresponding cell identities. Set to 0 to return unfiltered results.
- min_cells
int(default:5) Minimum cells (per cell identity if grouped by
groupby) to be considered for downstream analysis.- groupby_pairs
DataFrame|None(default:None) A DataFrame with columns
sourceandtargetto be used to subset the possible combinations of interacting cell types. If None, all possible combinations are used.- base
float(default:np.float64(2.718281828459045)) Exponent base used to reverse the log-transformation of the matrix. Relevant only for the
logfcmethod.- supp_columns
list[str] |None(default:None) Additional columns to be added from any of the methods implemented in liana, or any of the columns returned by
scanpy.tl.rank_genes_groups, each starting with ligand_* or receptor_*. For example,['ligand_pvals', 'receptor_pvals']. None by default.- return_all_lrs
bool(default:False) Bool whether to return all ligand-receptor pairs, or only those that surpass the
expr_propthreshold. Ligand-receptor pairs that do not pass theexpr_propthreshold will be assigned to the worst score of the ones that do.Falseby default.- key_added
str(default:'liana_res') Key under which the results will be stored in
adata.unsifinplaceis True.- use_raw
bool(default:False) Whether to use the
.rawattribute of adata. Defaults to False (uses.X).- layer
str|None(default:None) Layer in anndata.AnnData.layers to use. If None, use anndata.AnnData.X.
- de_method
Literal['logreg','t-test','wilcoxon','t-test_overestim_var'] (default:'t-test') Differential expression method.
scanpy.tl.rank_genes_groupsis used to rank genes according to 1vsRest. The default method is ‘t-test’.- n_perms
int|None(default:1000) Number of permutations for the permutation test. If None, no p-values are computed.
- seed
int(default:1337) Random seed for reproducibility.
- n_jobs
int(default:1) Number of jobs to run in parallel.
- resource
DataFrame|None(default:None) A pandas dataframe with [
ligand,receptor] columns. If provided will overrule the resource requested viaresource_name- interactions
list[tuple[str,str]] |None(default:None) List of tuples with ligand-receptor pairs
[(ligand, receptor), ...]to be used for the analysis. If passed, it will overrule the resource requested viaresourceandresource_name.- spatial_key
str|None(default:None) Key in
adata.obsmthat contains the spatial coordinates.- spatial_kwargs
SpatialKwargs|None(default:None) Keyword arguments passed to
liana.pp.spatial_pair_proximity()for computing spatial proximity weights. Default is None, which uses default values (bandwidth=250, kernel=’gaussian’, trim_fraction=0.1).- mdata_kwargs
MdataKwargs|None(default:None) Keyword arguments to be passed to
li.ms.mdata_to_anndataifadatais an instance ofMuData. If an AnnData object is passed, these arguments are ignored.- inplace
bool(default:True) Whether to store results in place, or else to return them.
- verbose
bool(default:False) Verbosity flag.
- adata
- Return type:
- Returns:
If
inplace = False, returns aDataFramewith ligand-receptor results Otherwise, modifies theadataobject with the following key:anndata.AnnData.uns[`key_added`]with the aforementioned DataFrame
Examples
Every method instance is called the same way;
cellphonedbshown here:>>> import liana as li >>> adata = li.ds.generate_toy_adata() >>> li.mt.cellphonedb(adata, groupby="bulk_labels", n_perms=100)