LIANA functions

scanpy_minion/pl/liana_cc_dotplot.py

@@ -0,0 +1,26 @@
+def liana_cc_dotplot(adata, 
+                     source_celltype:str list, 
+                     target_celltype: str list, **kwargs):
+
+    """
+    Plot LIANA results
+    adata: anndata obj
+    source_celltype: celltype(s) to be used as ligands (string)
+    target_celltype: celltype(s) to be used as ligands (string)
+
+    return: dotplot with LR results
+    """
+
+
+    li.pl.dotplot(adata = adata_filtered_dr,
+              colour='magnitude_rank',
+              size='specificity_rank',
+              inverse_size=True,
+              inverse_colour=True,
+              source_labels=source_celltype,
+              target_labels=target_celltype,
+              top_n=30,
+              orderby='magnitude_rank',
+              orderby_ascending=True,
+              figure_size=(8, 9)
+             )

scanpy_minion/tl/__init__.py

@@ -5,3 +5,4 @@
 from .map_to_dahlin import * # Map to dahlin
 from .tryumap import * # umap from scaling
 from .scvi import * # scvi
+from .liana_cc_rankaggr import * #Run LIANA

scanpy_minion/tl/liana_cc_rankaggr.py

@@ -0,0 +1,24 @@
+from anndata import AnnData
+from typing import Union
+
+
+def liana_cc_rankaggr(adata: AnnData,
+    use_raw: bool = False,
+    groupby: str,
+    resource_name: str):
+    """
+
+    """
+    This function calculates consensus ligand-receptor predictions  of individual methods. This is done by ranking and aggregating (RRA) the ligand-receptor interaction predictions from all methods.
+    adata: anndata obj
+
+    return: anndata with liana ligand-receptor interactions consensus results
+    """
+    import liana as li
+    li.mt.rank_aggregate(adata_filtered_dr,use_raw=False,
+		     groupby=groupby,
+		     resource_name='consensus',
+		     expr_prop=0.1
+		     verbose=True, **kwargs)
+    rank_aggregate.describe()
+