diff options
| -rw-r--r-- | gn3/computations/partial_correlations.py | 81 |
1 files changed, 39 insertions, 42 deletions
diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index e6056d5..13def5e 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -20,7 +20,7 @@ from gn3.function_helpers import compose from gn3.data_helpers import parse_csv_line from gn3.db.traits import export_informative from gn3.db.datasets import retrieve_trait_dataset -from gn3.db.traits import retrieve_trait_info, retrieve_trait_data +from gn3.db.partial_correlations import traits_info, traits_data from gn3.db.species import species_name, translate_to_mouse_gene_id from gn3.db.correlations import ( get_filename, @@ -608,18 +608,24 @@ def partial_correlations_entry(# pylint: disable=[R0913, R0914, R0911] threshold = 0 corr_min_informative = 4 - primary_trait = retrieve_trait_info(threshold, primary_trait_name, conn) - group = primary_trait["group"] - primary_trait_data = retrieve_trait_data(primary_trait, conn) + all_traits = traits_info( + conn, threshold, (primary_trait_name,) + control_trait_names) + all_traits_data = traits_data(conn, all_traits) + + primary_trait = tuple( + trait for trait in all_traits + if trait["trait_fullname"] == primary_trait_name)[0] + group = primary_trait["db"]["group"] + primary_trait_data = all_traits_data[primary_trait["trait_name"]] primary_samples, primary_values, _primary_variances = export_informative( primary_trait_data) cntrl_traits = tuple( - retrieve_trait_info(threshold, trait_full_name, conn) - for trait_full_name in control_trait_names) + trait for trait in all_traits + if trait["trait_fullname"] != primary_trait_name) cntrl_traits_data = tuple( - retrieve_trait_data(cntrl_trait, conn) - for cntrl_trait in cntrl_traits) + data for trait_name, data in all_traits_data.items() + if trait_name != primary_trait["trait_name"]) species = species_name(conn, group) (cntrl_samples, @@ -660,8 +666,8 @@ def partial_correlations_entry(# pylint: disable=[R0913, R0914, R0911] "traits."), "error_type": "Identical Traits"} - input_trait_geneid = primary_trait.get("geneid") - input_trait_symbol = primary_trait.get("symbol") + input_trait_geneid = primary_trait.get("geneid", 0) + input_trait_symbol = primary_trait.get("symbol", "") input_trait_mouse_geneid = translate_to_mouse_gene_id( species, input_trait_geneid, conn) @@ -682,7 +688,7 @@ def partial_correlations_entry(# pylint: disable=[R0913, R0914, R0911] "error_type": "Correlation Type"} if (method.lower() == "sgo literature correlation" and ( - input_trait_geneid is None or + bool(input_trait_geneid) is False or check_for_literature_info(conn, input_trait_mouse_geneid))): return { "status": "error", @@ -695,7 +701,7 @@ def partial_correlations_entry(# pylint: disable=[R0913, R0914, R0911] method.lower() in ( "tissue correlation, pearson's r", "tissue correlation, spearman's rho") - and input_trait_symbol is None): + and bool(input_trait_symbol) is False): return { "status": "error", "message": ( @@ -733,33 +739,19 @@ def partial_correlations_entry(# pylint: disable=[R0913, R0914, R0911] def __make_sorter__(method): - def __compare_lit_or_tiss_correlation_values_(row): - # Index Content - # 0 trait name - # 1 N - # 2 partial correlation coefficient - # 3 p value of partial correlation - # 6 literature/tissue correlation value - return (row[6], row[3]) - - def __compare_partial_correlation_p_values__(row): - # Index Content - # 0 trait name - # 1 partial correlation coefficient - # 2 N - # 3 p value of partial correlation + def __sort_6__(row): + return row[6] + + def __sort_3__(row): return row[3] if "literature" in method.lower(): - return __compare_lit_or_tiss_correlation_values_ + return __sort_6__ if "tissue" in method.lower(): - return __compare_lit_or_tiss_correlation_values_ - - return __compare_partial_correlation_p_values__ + return __sort_6__ - sorted_correlations = sorted( - all_correlations, key=__make_sorter__(method)) + return __sort_3__ add_lit_corr_and_tiss_corr = compose( partial(literature_correlation_by_list, conn, species), @@ -767,12 +759,11 @@ def partial_correlations_entry(# pylint: disable=[R0913, R0914, R0911] tissue_correlation_by_list, conn, input_trait_symbol, tissue_probeset_freeze_id, method)) - trait_list = add_lit_corr_and_tiss_corr(tuple( - { - **retrieve_trait_info( - threshold, - f"{target_dataset['dataset_name']}::{item[0]}", - conn), + selected_results = sorted( + all_correlations, + key=__make_sorter__(method))[:min(criteria, len(all_correlations))] + traits_list_corr_info = { + "{target_dataset['dataset_name']}::{item[0]}": { "noverlap": item[1], "partial_corr": item[2], "partial_corr_p_value": item[3], @@ -785,9 +776,15 @@ def partial_correlations_entry(# pylint: disable=[R0913, R0914, R0911] if len(item) == 8 else {}), **({"l_corr": item[6]} if len(item) == 7 else {}) - } - for item in - sorted_correlations[:min(criteria, len(all_correlations))])) + } for item in selected_results} + + trait_list = add_lit_corr_and_tiss_corr(tuple( + {**trait, **traits_list_corr_info.get(trait["trait_fullname"], {})} + for trait in traits_info( + conn, threshold, + tuple( + f"{target_dataset['dataset_name']}::{item[0]}" + for item in selected_results)))) return { "status": "success", |