diff options
Diffstat (limited to 'gn3')
| -rw-r--r-- | gn3/computations/correlations.py | 27 |
1 files changed, 20 insertions, 7 deletions
diff --git a/gn3/computations/correlations.py b/gn3/computations/correlations.py index a311b8d..804716c 100644 --- a/gn3/computations/correlations.py +++ b/gn3/computations/correlations.py @@ -150,7 +150,11 @@ def compute_all_sample_correlation(this_trait, corr_results.append({"trait_name_key": corr_result}) - return corr_results + sorted_corr_results = sorted( + corr_results, + key=lambda trait_name: -abs(list(trait_name.values())[0]["corr_coeffient"])) + return sorted_corr_results + def benchmark_compute_all_sample(this_trait, target_dataset, @@ -234,8 +238,8 @@ def tissue_correlation_for_trait_list( lit_corr_result = { "tissue_corr": tissue_corr_coeffient, - "p_value": p_value, - "tissue_number": len(primary_tissue_vals) + "tissue_number": len(primary_tissue_vals), + "p_value": p_value } return lit_corr_result @@ -291,6 +295,7 @@ def lit_correlation_for_trait_list( species=species, gene_id=trait_gene_id) + for (trait_name, target_trait_gene_id) in target_trait_lists: corr_results = {} if target_trait_gene_id: @@ -359,8 +364,11 @@ def compute_all_lit_correlation(conn, trait_lists: List, target_trait_lists=trait_lists, species=species, trait_gene_id=gene_id) + sorted_lit_results = sorted( + lit_results, + key=lambda trait_name: -abs(list(trait_name.values())[0]["lit_corr"])) - return {"lit_results": lit_results} + return sorted_lit_results def compute_all_tissue_correlation(primary_tissue_dict: dict, @@ -372,7 +380,7 @@ def compute_all_tissue_correlation(primary_tissue_dict: dict, """ - tissues_results = {} + tissues_results = [] primary_tissue_vals = primary_tissue_dict["tissue_values"] traits_symbol_dict = target_tissues_data["trait_symbol_dict"] @@ -391,9 +399,14 @@ def compute_all_tissue_correlation(primary_tissue_dict: dict, target_tissues_values=target_tissue_vals, corr_method=corr_method) - tissues_results[trait_id] = tissue_result + tissue_result_dict = {trait_id: tissue_result} + tissues_results.append(tissue_result_dict) + + sorted_tissues_results = sorted( + tissues_results, + key=lambda trait_name: -abs(list(trait_name.values())[0]["tissue_corr"])) - return tissues_results + return sorted_tissues_results def process_trait_symbol_dict(trait_symbol_dict, symbol_tissue_vals_dict) -> List: |