Sync error handling for gene variance and PCA to main

bin/post_process_sce.R

@@ -232,27 +232,38 @@ if (alt_exp %in% altExpNames(processed_sce)) {
 
 # Perform dimension reduction --------------------
 
-# model gene variance using `scran:modelGeneVar()`
-gene_variance <- scran::modelGeneVar(processed_sce)
-
-# select the most variable genes
-var_genes <- scran::getTopHVGs(gene_variance, n = opt$n_hvg)
-
-# save the most variable genes to the metadata
-metadata(processed_sce)$highly_variable_genes <- var_genes
-
-# dimensionality reduction
-# highly variable genes are used as input to PCA
-processed_sce <- scater::runPCA(processed_sce,
-                               ncomponents = opt$n_pcs,
-                               subset_row = var_genes)
+try({
+  # model gene variance using `scran:modelGeneVar()`
+  gene_variance <- scran::modelGeneVar(processed_sce)
+
+  # select the most variable genes
+  var_genes <- scran::getTopHVGs(gene_variance, n = opt$n_hvg)
+
+  # save the most variable genes to the metadata
+  metadata(processed_sce)$highly_variable_genes <- var_genes
+
+  # dimensionality reduction
+  # highly variable genes are used as input to PCA
+  processed_sce <- scater::runPCA(
+    processed_sce,
+    ncomponents = opt$n_pcs,
+    subset_row = var_genes
+  )
+})
 
-# calculate a UMAP matrix using the PCA results
 try({
-  processed_sce <- scater::runUMAP(processed_sce,
-                                  dimred = "PCA")
+  # calculate a UMAP matrix using the PCA results
+  processed_sce <- scater::runUMAP(
+    processed_sce,
+    dimred = "PCA"
+  )
 })
 
+# print a warning if no embeddings present
+if(length(reducedDimNames(processed_sce)) == 0){
+  warning("Reduced dimensions could not be calculated for this object.")
+}
+
 # Export --------------
 
 # write out _original_ filtered SCE with additional filtering column