diff options
Diffstat (limited to 'gn3/db')
| -rw-r--r-- | gn3/db/correlations.py | 183 |
1 files changed, 181 insertions, 2 deletions
diff --git a/gn3/db/correlations.py b/gn3/db/correlations.py index 67cfef9..87ab082 100644 --- a/gn3/db/correlations.py +++ b/gn3/db/correlations.py @@ -3,9 +3,11 @@ This module will hold functions that are used in the (partial) correlations feature to access the database to retrieve data needed for computations. """ -from typing import Any +from functools import reduce +from typing import Any, Dict, Tuple from gn3.random import random_string +from gn3.data_helpers import partition_all from gn3.db.species import translate_to_mouse_gene_id def get_filename(target_db_name: str, conn: Any) -> str: @@ -136,4 +138,181 @@ def fetch_literature_correlations( 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} + return dict(results) + +def compare_tissue_correlation_absolute_values(val1, val2): + """ + Comparison function for use when sorting tissue correlation values. + + This is a partial migration of the + `web.webqtl.correlation.CorrelationPage.getTempTissueCorrTable` function in + GeneNetwork1.""" + try: + if abs(val1) < abs(val2): + return 1 + if abs(val1) == abs(val2): + return 0 + return -1 + except TypeError: + return 0 + +def fetch_symbol_value_pair_dict( + symbol_list: Tuple[str, ...], data_id_dict: dict, + conn: Any) -> Dict[str, Tuple[float, ...]]: + """ + Map each gene symbols to the corresponding tissue expression data. + + This is a migration of the + `web.webqtl.correlation.correlationFunction.getSymbolValuePairDict` function + in GeneNetwork1. + """ + data_ids = { + symbol: data_id_dict.get(symbol) for symbol in symbol_list + if data_id_dict.get(symbol) is not None + } + query = "SELECT Id, value FROM TissueProbeSetData WHERE Id IN %(data_ids)s" + with conn.cursor() as cursor: + cursor.execute( + query, + data_ids=tuple(data_ids.values())) + value_results = cursor.fetchall() + return { + key: tuple(row[1] for row in value_results if row[0] == key) + for key in data_ids.keys() + } + + return {} + +def fetch_gene_symbol_tissue_value_dict( + symbol_list: Tuple[str, ...], data_id_dict: dict, conn: Any, + limit_num: int = 1000) -> dict:#getGeneSymbolTissueValueDict + """ + Wrapper function for `gn3.db.correlations.fetch_symbol_value_pair_dict`. + + This is a migrations of the + `web.webqtl.correlation.correlationFunction.getGeneSymbolTissueValueDict` in + GeneNetwork1. + """ + count = len(symbol_list) + if count != 0 and count <= limit_num: + return fetch_symbol_value_pair_dict(symbol_list, data_id_dict, conn) + + if count > limit_num: + return { + key: value for dct in [ + fetch_symbol_value_pair_dict(sl, data_id_dict, conn) + for sl in partition_all(limit_num, symbol_list)] + for key, value in dct.items() + } + + return {} + +def fetch_tissue_probeset_xref_info( + gene_name_list: Tuple[str, ...], probeset_freeze_id: int, + conn: Any) -> Tuple[tuple, dict, dict, dict, dict, dict, dict]: + """ + Retrieve the ProbeSet XRef information for tissues. + + This is a migration of the + `web.webqtl.correlation.correlationFunction.getTissueProbeSetXRefInfo` + function in GeneNetwork1.""" + with conn.cursor() as cursor: + if len(gene_name_list) == 0: + query = ( + "SELECT t.Symbol, t.GeneId, t.DataId, t.Chr, t.Mb, " + "t.description, t.Probe_Target_Description " + "FROM " + "(" + " SELECT Symbol, max(Mean) AS maxmean " + " FROM TissueProbeSetXRef " + " WHERE TissueProbeSetFreezeId=%(probeset_freeze_id)s " + " AND Symbol != '' " + " AND Symbol IS NOT NULL " + " GROUP BY Symbol" + ") AS x " + "INNER JOIN TissueProbeSetXRef AS t ON t.Symbol = x.Symbol " + "AND t.Mean = x.maxmean") + cursor.execute(query, probeset_freeze_id=probeset_freeze_id) + else: + query = ( + "SELECT t.Symbol, t.GeneId, t.DataId, t.Chr, t.Mb, " + "t.description, t.Probe_Target_Description " + "FROM " + "(" + " SELECT Symbol, max(Mean) AS maxmean " + " FROM TissueProbeSetXRef " + " WHERE TissueProbeSetFreezeId=%(probeset_freeze_id)s " + " AND Symbol in %(symbols)s " + " GROUP BY Symbol" + ") AS x " + "INNER JOIN TissueProbeSetXRef AS t ON t.Symbol = x.Symbol " + "AND t.Mean = x.maxmean") + cursor.execute( + query, probeset_freeze_id=probeset_freeze_id, + symbols=tuple(gene_name_list)) + + results = cursor.fetchall() + + return reduce( + lambda acc, item: ( + acc[0] + (item[0],), + {**acc[1], item[0].lower(): item[1]}, + {**acc[1], item[0].lower(): item[2]}, + {**acc[1], item[0].lower(): item[3]}, + {**acc[1], item[0].lower(): item[4]}, + {**acc[1], item[0].lower(): item[5]}, + {**acc[1], item[0].lower(): item[6]}), + results or tuple(), + (tuple(), {}, {}, {}, {}, {}, {})) + +def correlations_of_all_tissue_traits() -> Tuple[dict, dict]: + """ + This is a migration of the + `web.webqtl.correlation.CorrelationPage.calculateCorrOfAllTissueTrait` + function in GeneNetwork1. + """ + raise Exception("Unimplemented!!!") + return ({}, {}) + +def build_temporary_tissue_correlations_table( + trait_symbol: str, probeset_freeze_id: int, method: str, + return_number: int, conn: Any) -> str: + """ + Build a temporary table to hold the tissue correlations data. + + This is a migration of the + `web.webqtl.correlation.CorrelationPage.getTempTissueCorrTable` function in + GeneNetwork1.""" + raise Exception("Unimplemented!!!") + return "" + +def fetch_tissue_correlations( + dataset: dict, trait_symbol: str, probeset_freeze_id: int, method: str, + return_number: int, conn: Any) -> dict: + """ + Pair tissue correlations data with a trait id string. + + This is a migration of the + `web.webqtl.correlation.CorrelationPage.fetchTissueCorrelations` function in + GeneNetwork1. + """ + temp_table = build_temporary_tissue_correlations_table( + trait_symbol, probeset_freeze_id, method, return_number, conn) + with conn.cursor() as cursor: + cursor.execute( + ( + f"SELECT ProbeSet.Name, {temp_table}.Correlation, " + f"{temp_table}.PValue " + "FROM (ProbeSet, ProbeSetXRef, ProbeSetFreeze) " + "LEFT JOIN {temp_table} ON {temp_table}.Symbol=ProbeSet.Symbol " + "WHERE ProbeSetFreeze.Name = %(db_name) " + "AND ProbeSetFreeze.Id=ProbeSetXRef.ProbeSetFreezeId " + "AND ProbeSet.Id = ProbeSetXRef.ProbeSetId " + "AND ProbeSet.Symbol IS NOT NULL " + "AND %s.Correlation IS NOT NULL"), + db_name=dataset["dataset_name"]) + results = cursor.fetchall() + cursor.execute("DROP TEMPORARY TABLE %s", temp_table) + return { + trait_name: (tiss_corr, tiss_p_val) + for trait_name, tiss_corr, tiss_p_val in results} |