fix clustering selection based on configs

config/config.yaml

@@ -69,7 +69,7 @@ clustree:
     numerical_aggregation_option: "mean" # aggregation function for numerical metadata, options: mean, median, max, min
 
 ##### cluster validation ####
-# Cluster validation using inrternal cluster indices is computationally very expensive.
+# Cluster validation using internal cluster indices is computationally very expensive.
 # To reduce complexity and increase performance as proportion of samples can be used for the internal cluster evaluation.
 sample_proportion: 1 # float 0-1, >500 samples should be included.
 
@@ -91,7 +91,6 @@ scatterplot2d:
     size: 1
     alpha: 1
 
-
 # specify features of interest, which values from the data, will be highlgihted in the 2D/3D plots
 # motivated by bioinformatics highlighting expression levels of marker genes (eg: ['PTPRC'])
 # if not used leave empty []

workflow/Snakefile

@@ -28,10 +28,10 @@ clustree_metadata_content = []
 indices_external = []
 indices_internal = []
 
-if len(config["leiden"]["metrics"])>0:
+if len(config["leiden"]["metrics"])>0 and all([leiden_metric in config["umap"]["metrics"] for leiden_metric in config["leiden"]["metrics"]]):
     cluster_methods.append("Leiden")
 
-if len(config["clustification"]["method"])!="":
+if len(config["clustification"]["method"])!="" and config["clustification"]["method"] in cluster_methods:
     cluster_methods.append("clustification")
 
 # Dimensionality Reduction: apply PCA, UMAP and densMAP sepcific visualization flags
@@ -67,7 +67,6 @@ if len(cluster_methods) > 0:
     if len(config["metadata_of_interest"])>0:
         clustree_content.append('custom')
 
-
 ruleorder: clustification > aggregate_clustering_results
 
 rule all: