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 = {} if len(id_list) > 0: 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)