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-rw-r--r--gn3/db/correlations.py113
1 files changed, 113 insertions, 0 deletions
diff --git a/gn3/db/correlations.py b/gn3/db/correlations.py
index fa8e7ca..67cfef9 100644
--- a/gn3/db/correlations.py
+++ b/gn3/db/correlations.py
@@ -4,6 +4,10 @@ feature to access the database to retrieve data needed for computations.
"""
from typing import Any
+
+from gn3.random import random_string
+from gn3.db.species import translate_to_mouse_gene_id
+
def get_filename(target_db_name: str, conn: Any) -> str:
"""
Retrieve the name of the reference database file with which correlations are
@@ -24,3 +28,112 @@ def get_filename(target_db_name: str, conn: Any) -> str:
fname=result[1].replace(' ', '_').replace('/', '_'))
return ""
+
+def build_temporary_literature_table(
+ species: str, gene_id: int, return_number: int, conn: Any) -> str:
+ """
+ Build and populate a temporary table to hold the literature correlation data
+ to be used in computations.
+
+ "This is a migration of the
+ `web.webqtl.correlation.CorrelationPage.getTempLiteratureTable` function in
+ GeneNetwork1.
+ """
+ def __translated_species_id(row, cursor):
+ if species == "mouse":
+ return row[1]
+ query = {
+ "rat": "SELECT rat FROM GeneIDXRef WHERE mouse=%s",
+ "human": "SELECT human FROM GeneIDXRef WHERE mouse=%d"}
+ if species in query.keys():
+ cursor.execute(query[species], row[1])
+ record = cursor.fetchone()
+ if record:
+ return record[0]
+ return None
+ return None
+
+ temp_table_name = f"TOPLITERATURE{random_string(8)}"
+ with conn.cursor as cursor:
+ mouse_geneid = translate_to_mouse_gene_id(species, gene_id, conn)
+ data_query = (
+ "SELECT GeneId1, GeneId2, value FROM LCorrRamin3 "
+ "WHERE GeneId1 = %(mouse_gene_id)s "
+ "UNION ALL "
+ "SELECT GeneId2, GeneId1, value FROM LCorrRamin3 "
+ "WHERE GeneId2 = %(mouse_gene_id)s "
+ "AND GeneId1 != %(mouse_gene_id)s")
+ cursor.execute(
+ (f"CREATE TEMPORARY TABLE {temp_table_name} ("
+ "GeneId1 int(12) unsigned, "
+ "GeneId2 int(12) unsigned PRIMARY KEY, "
+ "value double)"))
+ cursor.execute(data_query, mouse_gene_id=mouse_geneid)
+ literature_data = [
+ {"GeneId1": row[0], "GeneId2": row[1], "value": row[2]}
+ for row in cursor.fetchall()
+ if __translated_species_id(row, cursor)]
+
+ cursor.execute(
+ (f"INSERT INTO {temp_table_name} "
+ "VALUES (%(GeneId1)s, %(GeneId2)s, %(value)s)"),
+ literature_data[0:(2 * return_number)])
+
+ return temp_table_name
+
+def fetch_geno_literature_correlations(temp_table: str) -> str:
+ """
+ Helper function for `fetch_literature_correlations` below, to build query
+ for `Geno*` tables.
+ """
+ return (
+ f"SELECT Geno.Name, {temp_table}.value "
+ "FROM Geno, GenoXRef, GenoFreeze "
+ f"LEFT JOIN {temp_table} ON {temp_table}.GeneId2=ProbeSet.GeneId "
+ "WHERE ProbeSet.GeneId IS NOT NULL "
+ f"AND {temp_table}.value IS NOT NULL "
+ "AND GenoXRef.GenoFreezeId = GenoFreeze.Id "
+ "AND GenoFreeze.Name = %(db_name)s "
+ "AND Geno.Id=GenoXRef.GenoId "
+ "ORDER BY Geno.Id")
+
+def fetch_probeset_literature_correlations(temp_table: str) -> str:
+ """
+ Helper function for `fetch_literature_correlations` below, to build query
+ for `ProbeSet*` tables.
+ """
+ return (
+ f"SELECT ProbeSet.Name, {temp_table}.value "
+ "FROM ProbeSet, ProbeSetXRef, ProbeSetFreeze "
+ "LEFT JOIN {temp_table} ON {temp_table}.GeneId2=ProbeSet.GeneId "
+ "WHERE ProbeSet.GeneId IS NOT NULL "
+ "AND {temp_table}.value IS NOT NULL "
+ "AND ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id "
+ "AND ProbeSetFreeze.Name = %(db_name)s "
+ "AND ProbeSet.Id=ProbeSetXRef.ProbeSetId "
+ "ORDER BY ProbeSet.Id")
+
+def fetch_literature_correlations(
+ species: str, gene_id: int, dataset: dict, return_number: int,
+ conn: Any) -> dict:
+ """
+ Gather the literature correlation data and pair it with trait id string(s).
+
+ This is a migration of the
+ `web.webqtl.correlation.CorrelationPage.fetchLitCorrelations` function in
+ GeneNetwork1.
+ """
+ temp_table = build_temporary_literature_table(
+ species, gene_id, return_number, conn)
+ query_fns = {
+ "Geno": fetch_geno_literature_correlations,
+ # "Temp": fetch_temp_literature_correlations,
+ # "Publish": fetch_publish_literature_correlations,
+ "ProbeSet": fetch_probeset_literature_correlations}
+ with conn.cursor as cursor:
+ cursor.execute(
+ query_fns[dataset["dataset_type"]](temp_table),
+ db_name=dataset["dataset_name"])
+ results = cursor.fetchall()
+ cursor.execute("DROP TEMPORARY TABLE %s", temp_table)
+ return dict(results) # {trait_name: lit_corr for trait_name, lit_corr in results}