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-rw-r--r--gn3/computations/partial_correlations.py55
-rw-r--r--gn3/db/partial_correlations.py2
2 files changed, 55 insertions, 2 deletions
diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py
index f82031a..0041684 100644
--- a/gn3/computations/partial_correlations.py
+++ b/gn3/computations/partial_correlations.py
@@ -19,8 +19,8 @@ from gn3.settings import TEXTDIR
from gn3.random import random_string
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 export_trait_data, export_informative
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 (
@@ -807,3 +807,56 @@ def partial_correlations_with_target_db(# pylint: disable=[R0913, R0914, R0911]
"dataset_type": target_dataset["type"],
"method": "spearman" if "spearman" in method.lower() else "pearson"
}}
+
+
+def partial_correlations_with_target_traits(
+ conn: Any, primary_trait_name: str,
+ control_trait_names: Tuple[str, ...],
+ target_trait_names: Tuple[str, ...], method: str) -> dict:
+ """
+ Compute partial correlation against a specific selection of traits.
+ """
+ threshold = 0
+ check_res = check_for_common_errors(
+ conn, primary_trait_name, control_trait_names)
+ if check_res.get("status") == "error":
+ return error_check_results
+
+ target_traits = {
+ trait["name"]: trait
+ for trait in traits_info(conn, threshold, target_trait_names)}
+ target_traits_data = traits_data(conn, target_traits.values())
+
+ def __merge(trait, pcorrs):
+ return {
+ **trait,
+ "noverlap": pcorrs[1],
+ "partial_corr": pcorrs[2],
+ "partial_corr_p_value": pcorrs[3],
+ "corr": pcorrs[4],
+ "corr_p_value": pcorrs[5]}
+
+ all_pcorrs = (
+ __merge(
+ target_traits[target_name],
+ compute_trait_info(
+ check_res["primary_values"], check_res["fixed_control_values"],
+ (export_trait_data(
+ target_data,
+ samplelist=check_res["common_primary_control_samples"]),
+ target_name),
+ method))
+ for target_name, target_data in target_traits_data.items())
+
+ return {
+ "status": "success",
+ "results": {
+ "primary_trait": trait_for_output(check_res["primary_trait"]),
+ "control_traits": tuple(
+ trait_for_output(trait) for trait in
+ check_res["control_traits"]),
+ "correlations": tuple(
+ trait_for_output(trait) for trait in all_pcorrs),
+ "dataset_type": "NOT SET YET",
+ "method": "spearman" if "spearman" in method.lower() else "pearson"
+ }}
diff --git a/gn3/db/partial_correlations.py b/gn3/db/partial_correlations.py
index 72dbf1a..96f953d 100644
--- a/gn3/db/partial_correlations.py
+++ b/gn3/db/partial_correlations.py
@@ -783,7 +783,7 @@ def traits_info(
partial(temp_traits_info, conn),
partial(temp_traits_datasets, conn, threshold))
}
- return tuple(
+ return (
trait for sublist in (# type: ignore[var-annotated]
traits_fns[dataset_type](traits)
for dataset_type, traits