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-rw-r--r--wqflask/wqflask/correlation/correlation_gn3_api.py31
1 files changed, 17 insertions, 14 deletions
diff --git a/wqflask/wqflask/correlation/correlation_gn3_api.py b/wqflask/wqflask/correlation/correlation_gn3_api.py
index aea91220..c96da8ee 100644
--- a/wqflask/wqflask/correlation/correlation_gn3_api.py
+++ b/wqflask/wqflask/correlation/correlation_gn3_api.py
@@ -149,7 +149,6 @@ def fetch_sample_data(start_vars, this_trait, this_dataset, target_dataset):
sample_data = test_process_data(this_trait, this_dataset, start_vars)
-
if target_dataset.type == "ProbeSet":
target_dataset.get_probeset_data(list(sample_data.keys()))
else:
@@ -202,17 +201,22 @@ def compute_correlation(start_vars, method="pearson", compute_all=False):
if tissue_input is not None:
(primary_tissue_data, target_tissue_data) = tissue_input
- corr_input_data = {
- "primary_tissue": primary_tissue_data,
- "target_tissues_dict": target_tissue_data
- }
- correlation_results = compute_tissue_correlation(
- primary_tissue_dict=corr_input_data["primary_tissue"],
- target_tissues_data=corr_input_data[
- "target_tissues_dict"],
- corr_method=method
-
- )
+ corr_input_data = {
+ "primary_tissue": primary_tissue_data,
+ "target_tissues_dict": target_tissue_data
+ }
+ correlation_results = compute_tissue_correlation(
+ primary_tissue_dict=corr_input_data["primary_tissue"],
+ target_tissues_data=corr_input_data[
+ "target_tissues_dict"],
+ corr_method=method
+
+ )
+ else:
+ return {"correlation_results": [],
+ "this_trait": this_trait.name,
+ "target_dataset": start_vars['corr_dataset'],
+ "return_results": corr_return_results}
elif corr_type == "lit":
(this_trait_geneid, geneid_dict, species) = do_lit_correlation(
@@ -302,5 +306,4 @@ def get_tissue_correlation_input(this_trait, trait_symbol_dict):
"trait_symbol_dict": trait_symbol_dict,
"symbol_tissue_vals_dict": corr_result_tissue_vals_dict
}
- return (primary_tissue_data, target_tissue_data)
- return None
+ return (primary_tissue_data, target_tissue_data) \ No newline at end of file