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author | Frederick Muriuki Muriithi | 2021-10-25 12:38:24 +0300 |
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committer | Frederick Muriuki Muriithi | 2021-10-25 12:38:24 +0300 |
commit | 0814eea6b57e45d4337424e63c164d204d03b64d (patch) | |
tree | d712f2333aaeafb0dcac7a1c4bf2065c1a3b4f51 /gn3/db/correlations.py | |
parent | df8185078a52c89cc5a75ff9be413a236da29a6e (diff) | |
download | genenetwork3-0814eea6b57e45d4337424e63c164d204d03b64d.tar.gz |
Implement `fetch_literature_correlations` and depedencies
Issue:
https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi
* Migrate:
* `web.webqtl.correlation.CorrelationPage.getTempLiteratureTable`
* `web.webqtl.correlation.CorrelationPage.fetchLitCorrelations`
from GeneNetwork1.
The first function creates and populates a temporary table with the
literature correlations data.
The second function uses the data in the newly created temporary table to
link the trait with the correlation value.
Diffstat (limited to 'gn3/db/correlations.py')
-rw-r--r-- | gn3/db/correlations.py | 113 |
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} |