Merge pull request #2 from glrs/main

Hotfix: Direct CellRanger output to the intended directory (TenX module)

lib/realms/tenx/run_sample.py

@@ -199,7 +199,7 @@ async def process(self):
         slurm_metadata = {
             "sample_id": self.run_sample_id,
             "project_name": self.project_info.get("project_name", ""),
-            "output_dir": str(self.file_handler.sample_dir),
+            "output_dir": str(self.file_handler.base_dir),
             "cellranger_command": cellranger_command,
         }
 
@@ -258,6 +258,9 @@ def assemble_cellranger_command(self) -> str:
         required_args = self.pipeline_info.get("required_arguments", [])
         additional_args = self.pipeline_info.get("fixed_arguments", [])
 
+        # Add output directory argument
+        additional_args.append(f"--output-dir={str(self.file_handler.sample_dir)}")
+
         # Mapping of argument names to their values
         arg_values: Dict[str, Any] = {
             "--id": self.run_sample_id,

lib/realms/tenx/tenx_project.py

@@ -289,6 +289,7 @@ def identify_feature_and_original_id_old(
             # Handle original samples without features
             library_prep_option = self.project_info.get("library_prep_option", "")
             feature = self.get_default_feature(library_prep_option)
+            # NOTE: If you want to name samples with the customer name, comment out the line below
             original_sample_id = sample_id
             return feature, original_sample_id
 
@@ -390,6 +391,7 @@ def extract_samples(self) -> List[TenXRunSample]:
         sample_data = self.filter_aborted_samples(sample_data)
         # Step 2: Create lab samples
         lab_samples = self.create_lab_samples(sample_data)
+        logging.info(f"Lab samples: {lab_samples}")
         # Step 3: Group lab samples by original sample ID
         grouped_lab_samples = self.group_lab_samples(lab_samples)
         # Step 4: Create run samples