- squidpy.gr.ligrec(adata, cluster_key, interactions=None, complex_policy='min', threshold=0.01, corr_method=None, corr_axis='clusters', use_raw=True, copy=False, key_added=None, gene_symbols=None, **kwargs)
Perform the permutation test as described in [Efremova et al., 2020].
AnnData) – Annotated data object.
Interaction to test. The type can be one of:
If None, the interactions are extracted from
omnipath. Protein complexes can be specified by delimiting the components with ‘_’, such as ‘alpha_beta_gamma’.
Literal[‘min’, ‘all’]) –
Policy on how to handle complexes. Valid options are:
’min’ - select gene with the minimum average expression. This is the same as in [Efremova et al., 2020].
’all’ - select all possible combinations between ‘source’ and ‘target’ complexes.
interactions_params – Keyword arguments for
omnipath.interactions.import_intercell_network()defining the interactions. These datasets from [Türei et al., 2016] are used by default: omnipath, pathwayextra, kinaseextra and ligrecextra.
transmitter_params – Keyword arguments for
omnipath.interactions.import_intercell_network()defining the transmitter side of intercellular connections.
receiver_params – Keyword arguments for
omnipath.interactions.import_intercell_network()defining the receiver side of intercellular connections.
n_perms – Number of permutations for the permutation test.
float) – Do not perform permutation test if any of the interacting components is being expressed in less than
thresholdpercent of cells within a given cluster.
seed – Random seed for reproducibility.
Literal[‘interactions’, ‘clusters’]) –
Axis over which to perform the FDR correction. Only used when
corr_method != None. Valid options are:
’interactions’ - correct interactions by performing FDR correction across the clusters.
’clusters’ - correct clusters by performing FDR correction across the interactions.
alpha – Significance level for FDR correction. Only used when
corr_method != None.
bool) – If
True, return the result, otherwise save it to the
numba_parallel – Whether to use
numba.prangeor not. If None, it is determined automatically. For small datasets or small number of interactions, it’s recommended to set this to False.
n_jobs – Number of parallel jobs.
backend – Parallelization backend to use. See
joblib.Parallelfor available options.
show_progress_bar – Whether to show the progress bar or not.
- Return type
copy = True, returns a
dictwith following keys:
Otherwise, modifies the
adataobject with the following key:
NaN p-values mark combinations for which the mean expression of one of the interacting components was 0 or it didn’t pass the
thresholdpercentage of cells being expressed within a given cluster.