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from __future__ import absolute_import, print_function, division
import collections
from flask import g
from utility import db_tools
from utility import Bunch
from MySQLdb import escape_string as escape
from pprint import pformat as pf
class MrnaAssayTissueData(object):
def __init__(self, gene_symbols=None):
self.gene_symbols = gene_symbols
self.have_data = False
if self.gene_symbols == None:
self.gene_symbols = []
#print("self.gene_symbols:", self.gene_symbols)
self.data = collections.defaultdict(Bunch)
#self.gene_id_dict ={}
#self.data_id_dict = {}
#self.chr_dict = {}
#self.mb_dict = {}
#self.desc_dict = {}
#self.probe_target_desc_dict = {}
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=1 and '''
# Note that inner join is necessary in this query to get distinct record in one symbol group
# with highest mean value
# Due to the limit size of TissueProbeSetFreezeId table in DB,
# performance of inner join is acceptable.MrnaAssayTissueData(gene_symbols=symbol_list)
if len(gene_symbols) == 0:
query += '''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;
'''
else:
in_clause = db_tools.create_in_clause(gene_symbols)
#ZS: This was in the query, not sure why: http://docs.python.org/2/library/string.html?highlight=lower#string.lower
query += ''' Symbol in {} group by Symbol)
as x inner join TissueProbeSetXRef as t on t.Symbol = x.Symbol
and t.Mean = x.maxmean;
'''.format(in_clause)
results = g.db.execute(query).fetchall()
lower_symbols = []
for gene_symbol in gene_symbols:
if gene_symbol != None:
lower_symbols.append(gene_symbol.lower())
for result in results:
symbol = result[0]
#if symbol.lower() in [gene_symbol.lower() for gene_symbol in gene_symbols]:
if symbol.lower() in lower_symbols:
#gene_symbols.append(symbol)
symbol = symbol.lower()
self.data[symbol].gene_id = result.GeneId
self.data[symbol].data_id = result.DataId
self.data[symbol].chr = result.Chr
self.data[symbol].mb = result.Mb
self.data[symbol].description = result.description
self.data[symbol].probe_target_description = result.Probe_Target_Description
print("self.data: ", pf(self.data))
###########################################################################
#Input: cursor, symbolList (list), dataIdDict(Dict)
#output: symbolValuepairDict (dictionary):one dictionary of Symbol and Value Pair,
# key is symbol, value is one list of expression values of one probeSet;
#function: get one dictionary whose key is gene symbol and value is tissue expression data (list type).
#Attention! All keys are lower case!
###########################################################################
def get_symbol_values_pairs(self):
id_list = [self.data[symbol].data_id for symbol in self.data]
print("id_list:", id_list)
symbol_values_dict = {}
query = """SELECT TissueProbeSetXRef.Symbol, TissueProbeSetData.value
FROM TissueProbeSetXRef, TissueProbeSetData
WHERE TissueProbeSetData.Id IN {} and
TissueProbeSetXRef.DataId = TissueProbeSetData.Id""".format(db_tools.create_in_clause(id_list))
print("TISSUE QUERY:", query)
results = g.db.execute(query).fetchall()
for result in results:
if result.Symbol.lower() not in symbol_values_dict:
symbol_values_dict[result.Symbol.lower()] = [result.value]
else:
symbol_values_dict[result.Symbol.lower()].append(result.value)
#for symbol in self.data:
# data_id = self.data[symbol].data_id
# symbol_values_dict[symbol] = self.get_tissue_values(data_id)
return symbol_values_dict
#def get_tissue_values(self, data_id):
# """Gets the tissue values for a particular gene"""
#
# tissue_values=[]
#
# query = """SELECT value, id
# FROM TissueProbeSetData
# WHERE Id IN {}""".format(db_tools.create_in_clause(data_id))
#
# #try :
# results = g.db.execute(query).fetchall()
# for result in results:
# tissue_values.append(result.value)
# #symbol_values_dict[symbol] = value_list
# #except:
# # symbol_values_pairs[symbol] = None
#
# return tissue_values
########################################################################################################
#input: cursor, symbolList (list), dataIdDict(Dict): key is symbol
#output: SymbolValuePairDict(dictionary):one dictionary of Symbol and Value Pair.
# key is symbol, value is one list of expression values of one probeSet.
#function: wrapper function for getSymbolValuePairDict function
# build gene symbol list if necessary, cut it into small lists if necessary,
# then call getSymbolValuePairDict function and merge the results.
########################################################################################################
#def get_trait_symbol_and_tissue_values(symbol_list=None):
# tissue_data = MrnaAssayTissueData(gene_symbols=symbol_list)
#
# #symbolList,
# #geneIdDict,
# #dataIdDict,
# #ChrDict,
# #MbDict,
# #descDict,
# #pTargetDescDict = getTissueProbeSetXRefInfo(
# # GeneNameLst=GeneNameLst,TissueProbeSetFreezeId=TissueProbeSetFreezeId)
#
# if len(tissue_data.gene_symbols):
# return get_symbol_values_pairs(tissue_data)
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