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-rwxr-xr-xweb/webqtl/correlation/CorrelationPage.py1143
1 files changed, 638 insertions, 505 deletions
diff --git a/web/webqtl/correlation/CorrelationPage.py b/web/webqtl/correlation/CorrelationPage.py
index 8ce669cb..42059117 100755
--- a/web/webqtl/correlation/CorrelationPage.py
+++ b/web/webqtl/correlation/CorrelationPage.py
@@ -23,6 +23,9 @@
# Created by GeneNetwork Core Team 2010/08/10
#
# Last updated by NL 2011/02/11
+# Last updated by Christian Fernandez 2012/04/07
+# Refactored correlation calculation into smaller functions in preparation of
+# separating html from existing code
import string
from math import *
@@ -47,447 +50,349 @@ from dbFunction import webqtlDatabaseFunction
import utility.webqtlUtil #this is for parallel computing only.
from correlation import correlationFunction
+import logging
+logging.basicConfig(filename="/tmp/gn_log", level=logging.INFO)
+_log = logging.getLogger("correlation")
-class CorrelationPage(templatePage):
-
- corrMinInformative = 4
-
- def __init__(self, fd):
-
- #XZ, 01/14/2009: This method is for parallel computing only.
- #XZ: It is supposed to be called when "Genetic Correlation, Pearson's r" (method 1)
- #XZ: or "Genetic Correlation, Spearman's rho" (method 2) is selected
- def compute_corr( input_nnCorr, input_trait, input_list, computing_method):
-
- allcorrelations = []
-
- for line in input_list:
- tokens = line.split('","')
- tokens[-1] = tokens[-1][:-2] #remove the last "
- tokens[0] = tokens[0][1:] #remove the first "
-
- traitdataName = tokens[0]
- database_trait = tokens[1:]
-
- if computing_method == "1": #XZ: Pearson's r
- corr,nOverlap = utility.webqtlUtil.calCorrelationText(input_trait, database_trait, input_nnCorr)
- else: #XZ: Spearman's rho
- corr,nOverlap = utility.webqtlUtil.calCorrelationRankText(input_trait, database_trait, input_nnCorr)
- traitinfo = [traitdataName,corr,nOverlap]
- allcorrelations.append(traitinfo)
-
- return allcorrelations
-
-
- templatePage.__init__(self, fd)
-
- if not self.openMysql():
- return
-
- if not fd.genotype:
- fd.readGenotype()
-
- #XZ, 09/18/2008: get the information such as value, variance of the input strain names from the form.
- if fd.allstrainlist:
- mdpchoice = fd.formdata.getvalue('MDPChoice')
- #XZ, in HTML source code, it is "BXD Only" or "BXH only", and so on
- if mdpchoice == "1":
- strainlist = fd.f1list + fd.strainlist
- #XZ, in HTML source code, it is "MDP Only"
- elif mdpchoice == "2":
- strainlist = []
- strainlist2 = fd.f1list + fd.strainlist
- for strain in fd.allstrainlist:
- if strain not in strainlist2:
- strainlist.append(strain)
- #So called MDP Panel
- if strainlist:
- strainlist = fd.f1list+fd.parlist+strainlist
- #XZ, in HTML source code, it is "All Cases"
- else:
- strainlist = fd.allstrainlist
- #XZ, 09/18/2008: put the trait data into dictionary fd.allTraitData
- fd.readData(fd.allstrainlist)
- else:
- mdpchoice = None
- strainlist = fd.strainlist
- #XZ, 09/18/2008: put the trait data into dictionary fd.allTraitData
- fd.readData()
-
- #XZ, 3/16/2010: variable RISet must be pass by the form
- RISet = fd.RISet
- #XZ, 12/12/2008: get species infomation
- species = webqtlDatabaseFunction.retrieveSpecies(cursor=self.cursor, RISet=RISet)
-
- #XZ, 09/18/2008: get all information about the user selected database.
- self.target_db_name = fd.formdata.getvalue('database')
-
- try:
- self.db = webqtlDataset(self.target_db_name, self.cursor)
- except:
- heading = "Correlation Table"
- detail = ["The database you just requested has not been established yet."]
- self.error(heading=heading,detail=detail)
- return
-
- #XZ, 09/18/2008: check if user has the authority to get access to the database.
- if self.db.type == 'ProbeSet':
- self.cursor.execute('SELECT Id, Name, FullName, confidentiality, AuthorisedUsers FROM ProbeSetFreeze WHERE Name = "%s"' % self.target_db_name)
- indId, indName, indFullName, confidential, AuthorisedUsers = self.cursor.fetchall()[0]
-
- if confidential == 1:
- access_to_confidential_dataset = 0
-
- #for the dataset that confidentiality is 1
- #1. 'admin' and 'root' can see all of the dataset
- #2. 'user' can see the dataset that AuthorisedUsers contains his id(stored in the Id field of User table)
- if webqtlConfig.USERDICT[self.privilege] > webqtlConfig.USERDICT['user']:
- access_to_confidential_dataset = 1
- else:
- AuthorisedUsersList=AuthorisedUsers.split(',')
- if AuthorisedUsersList.__contains__(self.userName):
- access_to_confidential_dataset = 1
-
- if not access_to_confidential_dataset:
- #Error, Confidential Database
- heading = "Correlation Table"
- detail = ["The %s database you selected is not open to the public at this time, please go back and select other database." % indFullName]
- self.error(heading=heading,detail=detail,error="Confidential Database")
- return
-
- #XZ, 09/18/2008: filter out the strains that have no value.
- _strains, _vals, _vars, N = fd.informativeStrains(strainlist)
-
- N = len(_strains)
-
- if N < self.corrMinInformative:
- heading = "Correlation Table"
- detail = ['Fewer than %d strain data were entered for %s data set. No calculation of correlation has been attempted.' % (self.corrMinInformative, RISet)]
- self.error(heading=heading,detail=detail)
- return
-
- #XZ, 09/28/2008: if user select "1", then display 1, 3 and 4.
- #XZ, 09/28/2008: if user select "2", then display 2, 3 and 5.
- #XZ, 09/28/2008: if user select "3", then display 1, 3 and 4.
- #XZ, 09/28/2008: if user select "4", then display 1, 3 and 4.
- #XZ, 09/28/2008: if user select "5", then display 2, 3 and 5.
- methodDict = {"1":"Genetic Correlation (Pearson's r)","2":"Genetic Correlation (Spearman's rho)","3":"SGO Literature Correlation","4":"Tissue Correlation (Pearson's r)", "5":"Tissue Correlation (Spearman's rho)"}
- self.method = fd.formdata.getvalue('method')
- if self.method not in ("1","2","3","4","5"):
- self.method = "1"
-
- self.returnNumber = int(fd.formdata.getvalue('criteria'))
-
- myTrait = fd.formdata.getvalue('fullname')
- if myTrait:
- myTrait = webqtlTrait(fullname=myTrait, cursor=self.cursor)
- myTrait.retrieveInfo()
-
- # We will not get Literature Correlations if there is no GeneId because there is nothing to look against
- try:
- input_trait_GeneId = int(fd.formdata.getvalue('GeneId'))
- except:
- input_trait_GeneId = None
-
- # We will not get Tissue Correlations if there is no gene symbol because there is nothing to look against
- try:
- input_trait_symbol = myTrait.symbol
- except:
- input_trait_symbol = None
-
-
- #XZ, 12/12/2008: if the species is rat or human, translate the geneid to mouse geneid
- input_trait_mouse_geneid = self.translateToMouseGeneID(species, input_trait_GeneId)
-
-
- #XZ: As of Nov/13/2010, this dataset is 'UTHSC Illumina V6.2 RankInv B6 D2 average CNS GI average (May 08)'
- TissueProbeSetFreezeId = 1
-
- #XZ, 09/22/2008: If we need search by GeneId,
- #XZ, 09/22/2008: we have to check if this GeneId is in the literature or tissue correlation table.
- #XZ, 10/15/2008: We also to check if the selected database is probeset type.
- if self.method == "3" or self.method == "4" or self.method == "5":
- if self.db.type != "ProbeSet":
- self.error(heading="Wrong correlation type",detail="It is not possible to compute the %s between your trait and data in this %s database. Please try again after selecting another type of correlation." % (methodDict[self.method],self.db.name),error="Correlation Type Error")
- return
-
- """
- if not input_trait_GeneId:
- self.error(heading="No Associated GeneId",detail="This trait has no associated GeneId, so we are not able to show any literature or tissue related information.",error="No GeneId Error")
- return
- """
-
- #XZ: We have checked geneid did exist
+debug_file = open("/home/zas1024/gn/web/corr_debug.txt","w")
+debug_file2 = open("/home/zas1024/gn/web/corr_debug2.txt","w")
- if self.method == "3":
- if not input_trait_GeneId or not self.checkForLitInfo(input_trait_mouse_geneid):
- self.error(heading="No Literature Info",detail="This gene does not have any associated Literature Information.",error="Literature Correlation Error")
- return
+METHOD_SAMPLE_PEARSON = "1"
+METHOD_SAMPLE_RANK = "2"
+METHOD_LIT = "3"
+METHOD_TISSUE_PEARSON = "4"
+METHOD_TISSUE_RANK = "5"
- if self.method == "4" or self.method == "5":
- if not input_trait_symbol:
- self.error(heading="No Tissue Correlation Information",detail="This gene does not have any associated Tissue Correlation Information.",error="Tissue Correlation Error")
- return
+TISSUE_METHODS = [METHOD_TISSUE_PEARSON, METHOD_TISSUE_RANK]
- if not self.checkSymbolForTissueCorr(TissueProbeSetFreezeId, myTrait.symbol):
- self.error(heading="No Tissue Correlation Information",detail="This gene does not have any associated Tissue Correlation Information.",error="Tissue Correlation Error")
- return
+TISSUE_MOUSE_DB = 1
-############################################################################################################################################
+class AuthException(Exception): pass
- allcorrelations = []
- nnCorr = len(_vals)
- #XZ: Use the fast method only for probeset dataset, and this dataset must have been created.
- #XZ: Otherwise, use original method
+class Trait(object):
+ def __init__(self, name, raw_values = None, lit_corr = None, tissue_corr = None, p_tissue = None):
+ self.name = name
+ self.raw_values = raw_values
+ self.lit_corr = lit_corr
+ self.tissue_corr = tissue_corr
+ self.p_tissue = p_tissue
+ self.correlation = 0
+ self.p_value = 0
- useFastMethod = False
+ @staticmethod
+ def from_csv(line, data_start = 1):
+ name = line[0]
+ numbers = line[data_start:]
+ # _log.info(numbers)
+ numbers = [ float(number) for number in numbers ]
- if self.db.type == "ProbeSet":
+ return Trait(name, raw_values = numbers)
- DatabaseFileName = self.getFileName( target_db_name=self.target_db_name )
- DirectoryList = os.listdir(webqtlConfig.TEXTDIR) ### List of existing text files. Used to check if a text file already exists
-
- if DatabaseFileName in DirectoryList:
- useFastMethod = True
-
- if useFastMethod:
- if 1:
- #try:
- useLit = False
- if self.method == "3":
- litCorrs = self.fetchLitCorrelations(species=species, GeneId=input_trait_GeneId, db=self.db, returnNumber=self.returnNumber)
- useLit = True
-
- useTissueCorr = False
- if self.method == "4" or self.method == "5":
- tissueCorrs = self.fetchTissueCorrelations(db=self.db, primaryTraitSymbol=input_trait_symbol, TissueProbeSetFreezeId=TissueProbeSetFreezeId, method=self.method, returnNumber = self.returnNumber)
- useTissueCorr = True
-
- datasetFile = open(webqtlConfig.TEXTDIR+DatabaseFileName,'r')
-
- #XZ, 01/08/2009: read the first line
- line = datasetFile.readline()
- dataset_strains = webqtlUtil.readLineCSV(line)[1:]
-
- #XZ, 01/08/2009: This step is critical. It is necessary for this new method.
- #XZ: The original function fetchAllDatabaseData uses all strains stored in variable _strains to
- #XZ: retrieve the values of each strain from database in real time.
- #XZ: The new method uses all strains stored in variable dataset_strains to create a new variable
- #XZ: _newvals. _newvals has the same length as dataset_strains. The items in _newvals is in
- #XZ: the same order of items in dataset_strains. The value of each item in _newvals is either
- #XZ: the value of correspinding strain in _vals or 'None'.
- _newvals = []
- for item in dataset_strains:
- if item in _strains:
- _newvals.append(_vals[_strains.index(item)])
- else:
- _newvals.append('None')
-
- nnCorr = len(_newvals)
+ def calculate_correlation(self, values, method):
+ """Calculate the correlation value and p value according to the method specified"""
- #XZ, 01/14/2009: If literature corr or tissue corr is selected,
- #XZ: there is no need to use parallel computing.
- if useLit or useTissueCorr:
- for line in datasetFile:
- traitdata=webqtlUtil.readLineCSV(line)
- traitdataName = traitdata[0]
- traitvals = traitdata[1:]
+ #ZS: This takes the list of values of the trait our selected trait is being correlated against and removes the values of the samples our trait has no value for
+ #There's probably a better way of dealing with this, but I'll have to ask Christian
+ updated_raw_values = []
+ updated_values = []
+ for i in range(len(values)):
+ if values[i] != "None":
+ updated_raw_values.append(self.raw_values[i])
+ updated_values.append(values[i])
- if useLit:
- if not litCorrs.has_key( traitdataName ):
- continue
+ self.raw_values = updated_raw_values
+ values = updated_values
- if useTissueCorr:
- if not tissueCorrs.has_key( traitdataName ):
- continue
-
- if self.method == "3" or self.method == "4":
- corr,nOverlap = webqtlUtil.calCorrelationText(traitvals,_newvals,nnCorr)
- else:
- corr,nOverlap = webqtlUtil.calCorrelationRankText(traitvals,_newvals,nnCorr)
-
- traitinfo = [traitdataName,corr,nOverlap]
-
- if useLit:
- traitinfo.append(litCorrs[traitdataName])
-
- if useTissueCorr:
- tempCorr, tempPValue = tissueCorrs[traitdataName]
- traitinfo.append(tempCorr)
- traitinfo.append(tempPValue)
+ if method == METHOD_SAMPLE_PEARSON or method == METHOD_LIT or method == METHOD_TISSUE_PEARSON:
+ corr,nOverlap = webqtlUtil.calCorrelation(self.raw_values, values, len(values))
+ else:
+ corr,nOverlap = webqtlUtil.calCorrelationRank(self.raw_values, values, len(values))
- allcorrelations.append(traitinfo)
- #XZ, 01/14/2009: If genetic corr is selected, use parallel computing
- else:
- input_line_list = datasetFile.readlines()
- all_line_number = len(input_line_list)
+ self.correlation = corr
+ self.overlap = nOverlap
- step = 1000
- job_number = math.ceil( float(all_line_number)/step )
+ if self.overlap < 3:
+ self.p_value = 1.0
+ else:
+ #ZS - This is probably the wrong way to deal with this. Correlation values of 1.0 definitely exist (the trait correlated against itself), so zero division needs to br prevented.
+ if abs(self.correlation) >= 1.0:
+ self.p_value = 0.0
+ else:
+ ZValue = 0.5*log((1.0+self.correlation)/(1.0-self.correlation))
+ ZValue = ZValue*sqrt(self.overlap-3)
+ self.p_value = 2.0*(1.0 - reaper.normp(abs(ZValue)))
- job_input_lists = []
+
- for job_index in range( int(job_number) ):
- starti = job_index*step
- endi = min((job_index+1)*step, all_line_number)
+#XZ, 01/14/2009: This method is for parallel computing only.
+#XZ: It is supposed to be called when "Genetic Correlation, Pearson's r" (method 1)
+#XZ: or "Genetic Correlation, Spearman's rho" (method 2) is selected
+def compute_corr( input_nnCorr, input_trait, input_list, computing_method):
+
+ allcorrelations = []
+
+ for line in input_list:
+ tokens = line.split('","')
+ tokens[-1] = tokens[-1][:-2] #remove the last "
+ tokens[0] = tokens[0][1:] #remove the first "
+
+ traitdataName = tokens[0]
+ database_trait = tokens[1:]
+
+ if computing_method == "1": #XZ: Pearson's r
+ corr,nOverlap = utility.webqtlUtil.calCorrelationText(input_trait, database_trait, input_nnCorr)
+ else: #XZ: Spearman's rho
+ corr,nOverlap = utility.webqtlUtil.calCorrelationRankText(input_trait, database_trait, input_nnCorr)
+ traitinfo = [traitdataName,corr,nOverlap]
+ allcorrelations.append(traitinfo)
+
+ return allcorrelations
+
+def get_correlation_method_key(form_data):
+ #XZ, 09/28/2008: if user select "1", then display 1, 3 and 4.
+ #XZ, 09/28/2008: if user select "2", then display 2, 3 and 5.
+ #XZ, 09/28/2008: if user select "3", then display 1, 3 and 4.
+ #XZ, 09/28/2008: if user select "4", then display 1, 3 and 4.
+ #XZ, 09/28/2008: if user select "5", then display 2, 3 and 5.
+
+ method = form_data.formdata.getvalue("method")
+ if method not in ["1", "2", "3" ,"4", "5"]:
+ return "1"
+
+ return method
+
+
+def get_custom_trait(form_data, cursor):
+ """Pulls the custom trait, if it exists, out of the form data"""
+ trait_name = form_data.formdata.getvalue('fullname')
+
+ if trait_name:
+ trait = webqtlTrait(fullname=trait_name, cursor=cursor)
+ trait.retrieveInfo()
+ return trait
+ else:
+ return None
+
+
+#XZ, 09/18/2008: get the information such as value, variance of the input strain names from the form.
+def get_sample_data(form_data):
+ if form_data.allstrainlist:
+ mdpchoice = form_data.formdata.getvalue('MDPChoice')
+ #XZ, in HTML source code, it is "BXD Only" or "BXH only", and so on
+ if mdpchoice == "1":
+ strainlist = form_data.f1list + form_data.strainlist
+ #XZ, in HTML source code, it is "MDP Only"
+ elif mdpchoice == "2":
+ strainlist = []
+ strainlist2 = form_data.f1list + form_data.strainlist
+ for strain in form_data.allstrainlist:
+ if strain not in strainlist2:
+ strainlist.append(strain)
+ #So called MDP Panel
+ if strainlist:
+ strainlist = form_data.f1list+form_data.parlist+strainlist
+ #XZ, in HTML source code, it is "All Cases"
+ else:
+ strainlist = form_data.allstrainlist
+ #XZ, 09/18/2008: put the trait data into dictionary form_data.allTraitData
+ form_data.readData(form_data.allstrainlist)
+ else:
+ mdpchoice = None
+ strainlist = form_data.strainlist
+ #XZ, 09/18/2008: put the trait data into dictionary form_data.allTraitData
+ form_data.readData()
+
+ return strainlist
+
+
+def get_mdp_choice(form_data):
+ if form_data.allstrainlist:
+ return form_data.formdata.getvalue("MDPChoice")
+ else:
+ return None
+
+
+def get_species(fd, cursor):
+ #XZ, 3/16/2010: variable RISet must be pass by the form
+ RISet = fd.RISet
+ #XZ, 12/12/2008: get species infomation
+ species = webqtlDatabaseFunction.retrieveSpecies(cursor=cursor, RISet=RISet)
+ return species
+
+
+def sortTraitCorrelations(traits, method="1"):
+ for trait in traits:
+ if trait.lit_corr != None and float(trait.lit_corr) > 0.6:
+ debug_file.write(str(trait.lit_corr) + "\n")
+ if method in TISSUE_METHODS:
+ #traits.sort(key=lambda trait: trait.tissue_corr != None and abs(float(trait.tissue_corr)) or 0)
+ traits.sort(key=lambda trait: trait.tissue_corr != None and abs(trait.tissue_corr), reverse=True)
+ elif method == METHOD_LIT:
+ #traits.sort(key=lambda trait: trait.lit_corr != None and abs(float(trait.lit_corr)) or 0)
+ traits.sort(key=lambda trait: trait.lit_corr != None and abs(trait.lit_corr), reverse=True)
+ else:
+ #traits.sort(key=lambda trait: trait.correlation != None and abs(float(trait.correlation)) or 0)
+ traits.sort(key=lambda trait: trait.correlation != None and abs(trait.correlation), reverse=True)
+
+ for trait in traits:
+ if trait.lit_corr != None and float(trait.lit_corr) > 0.6:
+ debug_file2.write(str(trait.lit_corr) + "\n")
+
+ return traits
+
+
+
+def cmpTraitCorr(A,B):
+ try:
+ if abs(A.correlation) < abs(B.correlation):
+ return 1
+ elif abs(A.correlation) == abs(B.correlation):
+ return 0
+ else:
+ return -1
+ except:
+ return 0
+
+def auth_user_for_db(db, cursor, target_db_name, privilege, username):
+ """Authorize a user for access to a database if that database is
+ confidential. A db (identified by a record in ProbeSetFreeze) contains a
+ list of authorized users who may access it, as well as its confidentiality
+ level.
+
+ If the current user's privilege level is greater than 'user', ie: root or
+ admin, then they are automatically authed, otherwise, check the
+ AuthorizedUsers field for the presence of their name."""
+
+ if db.type == 'ProbeSet':
+ cursor.execute('SELECT Id, Name, FullName, confidentiality, AuthorisedUsers FROM ProbeSetFreeze WHERE Name = "%s"' % target_db_name)
+ indId, indName, indFullName, confidential, AuthorisedUsers = cursor.fetchall()[0]
+
+ if confidential:
+ authorized = 0
+
+ #for the dataset that confidentiality is 1
+ #1. 'admin' and 'root' can see all of the dataset
+ #2. 'user' can see the dataset that AuthorisedUsers contains his id(stored in the Id field of User table)
+ if webqtlConfig.USERDICT[privilege] > webqtlConfig.USERDICT['user']:
+ authorized = 1
+ else:
+ if username in AuthorisedUsers.split(","):
+ authorized = 1
- one_job_input_list = []
+ if not authorized:
+ raise AuthException("The %s database you selected is not open to the public at this time, please go back and select other database." % indFullName)
- for i in range( starti, endi ):
- one_job_input_list.append( input_line_list[i] )
- job_input_lists.append( one_job_input_list )
+class CorrelationPage(templatePage):
- ppservers = ()
- # Creates jobserver with automatically detected number of workers
- job_server = pp.Server(ppservers=ppservers)
+ corrMinInformative = 4
- jobs = []
- results = []
+ PAGE_HEADING = "Correlation Table"
+ CORRELATION_METHODS = {"1" : "Genetic Correlation (Pearson's r)",
+ "2" : "Genetic Correlation (Spearman's rho)",
+ "3" : "SGO Literature Correlation",
+ "4" : "Tissue Correlation (Pearson's r)",
+ "5" : "Tissue Correlation (Spearman's rho)"}
- for one_job_input_list in job_input_lists: #pay attention to modules from outside
- jobs.append( job_server.submit(func=compute_corr, args=(nnCorr, _newvals, one_job_input_list, self.method), depfuncs=(), modules=("utility.webqtlUtil",)) )
+ RANK_ORDERS = {"1": 0, "2": 1, "3": 0, "4": 0, "5": 1}
- for one_job in jobs:
- one_result = one_job()
- results.append( one_result )
- for one_result in results:
- for one_traitinfo in one_result:
- allcorrelations.append( one_traitinfo )
+ def error(self, message, error="Error", heading = None):
+ heading = heading or self.PAGE_HEADING
+ return templatePage.error(heading = heading, detail = [message], error=error)
- datasetFile.close()
- totalTraits = len(allcorrelations)
- #except:
- # useFastMethod = False
- # self.error(heading="No computation method",detail="Something is wrong within the try except block in CorrelationPage python module.",error="Computation Error")
- # return
+ def __init__(self, fd):
- #XZ, 01/08/2009: use the original method to retrieve from database and compute.
- if not useFastMethod:
+ # Call the superclass constructor
+ templatePage.__init__(self, fd)
- traitdatabase, dataStartPos = self.fetchAllDatabaseData(species=species, GeneId=input_trait_GeneId, GeneSymbol=input_trait_symbol, strains=_strains, db=self.db, method=self.method, returnNumber=self.returnNumber, tissueProbeSetFreezeId=TissueProbeSetFreezeId)
+ # Connect to the database
+ if not self.openMysql():
+ return
- totalTraits = len(traitdatabase) #XZ, 09/18/2008: total trait number
+ # Read the genotype from a file
+ if not fd.genotype:
+ fd.readGenotype()
- for traitdata in traitdatabase:
- traitdataName = traitdata[0]
- traitvals = traitdata[dataStartPos:]
- if self.method == "1" or self.method == "3" or self.method == "4":
- corr,nOverlap = webqtlUtil.calCorrelation(traitvals,_vals,nnCorr)
- else:
- corr,nOverlap = webqtlUtil.calCorrelationRank(traitvals,_vals,nnCorr)
+ sample_list = get_sample_data(fd)
+ mdp_choice = get_mdp_choice(fd) # No idea what this is yet
+ self.species = get_species(fd, self.cursor)
- traitinfo = [traitdataName,corr,nOverlap]
+ #XZ, 09/18/2008: get all information about the user selected database.
+ target_db_name = fd.formdata.getvalue('database')
+ self.target_db_name = target_db_name
- #XZ, 09/28/2008: if user select '3', then fetchAllDatabaseData would give us LitCorr in the [1] position
- #XZ, 09/28/2008: if user select '4' or '5', then fetchAllDatabaseData would give us Tissue Corr in the [1] position
- #XZ, 09/28/2008: and Tissue Corr P Value in the [2] position
- if input_trait_GeneId and self.db.type == "ProbeSet":
- if self.method == "3":
- traitinfo.append( traitdata[1] )
- if self.method == "4" or self.method == "5":
- traitinfo.append( traitdata[1] )
- traitinfo.append( traitdata[2] )
+ try:
+ self.db = webqtlDataset(target_db_name, self.cursor)
+ except:
+ detail = ["The database you just requested has not been established yet."]
+ self.error(detail)
+ return
- allcorrelations.append(traitinfo)
+ # Auth if needed
+ try:
+ auth_user_for_db(self.db, self.cursor, target_db_name, self.privilege, self.userName)
+ except AuthException, e:
+ detail = [e.message]
+ return self.error(detail)
+ #XZ, 09/18/2008: filter out the strains that have no value.
+ self.sample_names, vals, vars, N = fd.informativeStrains(sample_list)
-#############################################################
+ #CF - If less than a minimum number of strains/cases in common, don't calculate anything
+ if len(self.sample_names) < self.corrMinInformative:
+ detail = ['Fewer than %d strain data were entered for %s data set. No calculation of correlation has been attempted.' % (self.corrMinInformative, fd.RISet)]
+ self.error(heading=PAGE_HEADING,detail=detail)
- if self.method == "3" and input_trait_GeneId:
- allcorrelations.sort(webqtlUtil.cmpLitCorr)
- #XZ, 3/31/2010: Theoretically, we should create one function 'comTissueCorr'
- #to compare each trait by their tissue corr p values.
- #But because the tissue corr p values are generated by permutation test,
- #the top ones always have p value 0. So comparing p values actually does nothing.
- #In addition, for the tissue data in our database, the N is always the same.
- #So it's safe to compare with tissue corr statistic value.
- #That's the same as literature corr.
- elif self.method in ["4","5"] and input_trait_GeneId:
- allcorrelations.sort(webqtlUtil.cmpLitCorr)
- else:
- allcorrelations.sort(webqtlUtil.cmpCorr)
+ self.method = get_correlation_method_key(fd)
+ correlation_method = self.CORRELATION_METHODS[self.method]
+ rankOrder = self.RANK_ORDERS[self.method]
- #XZ, 09/20/2008: we only need the top ones.
- self.returnNumber = min(self.returnNumber,len(allcorrelations))
- allcorrelations = allcorrelations[:self.returnNumber]
+ # CF - Number of results returned
+ self.returnNumber = int(fd.formdata.getvalue('criteria'))
- addLiteratureCorr = False
- addTissueCorr = False
+ self.record_count = 0
- traitList = []
- for item in allcorrelations:
- thisTrait = webqtlTrait(db=self.db, name=item[0], cursor=self.cursor)
- thisTrait.retrieveInfo( QTL='Yes' )
+ myTrait = get_custom_trait(fd, self.cursor)
- nOverlap = item[2]
- corr = item[1]
- #XZ: calculate corrPValue
- if nOverlap < 3:
- corrPValue = 1.0
- else:
- if abs(corr) >= 1.0:
- corrPValue = 0.0
- else:
- ZValue = 0.5*log((1.0+corr)/(1.0-corr))
- ZValue = ZValue*sqrt(nOverlap-3)
- corrPValue = 2.0*(1.0 - reaper.normp(abs(ZValue)))
-
- thisTrait.Name = item[0]
- thisTrait.corr = corr
- thisTrait.nOverlap = nOverlap
- thisTrait.corrPValue = corrPValue
- # NL, 07/19/2010
- # js function changed, add a new parameter rankOrder for js function 'showTissueCorrPlot'
- rankOrder = 0;
- if self.method in ["2","5"]:
- rankOrder = 1;
- thisTrait.rankOrder =rankOrder
-
- #XZ, 26/09/2008: Method is 4 or 5. Have fetched tissue corr, but no literature correlation yet.
- if len(item) == 5:
- thisTrait.tissueCorr = item[3]
- thisTrait.tissuePValue = item[4]
- addLiteratureCorr = True
+ # We will not get Literature Correlations if there is no GeneId because there is nothing to look against
+ self.gene_id = int(fd.formdata.getvalue('GeneId') or 0)
- #XZ, 26/09/2008: Method is 3, Have fetched literature corr, but no tissue corr yet.
- elif len(item) == 4:
- thisTrait.LCorr = item[3]
- thisTrait.mouse_geneid = self.translateToMouseGeneID(species, thisTrait.geneid)
- addTissueCorr = True
+ # We will not get Tissue Correlations if there is no gene symbol because there is nothing to look against
+ self.trait_symbol = myTrait.symbol
+
- #XZ, 26/09/2008: Method is 1 or 2. Have NOT fetched literature corr and tissue corr yet.
- # Phenotype data will not have geneid, and neither will some probes
- # we need to handle this because we will get an attribute error
- else:
- if input_trait_mouse_geneid and self.db.type=="ProbeSet":
- addLiteratureCorr = True
- if input_trait_symbol and self.db.type=="ProbeSet":
- addTissueCorr = True
+ #XZ, 12/12/2008: if the species is rat or human, translate the geneid to mouse geneid
+ self.input_trait_mouse_gene_id = self.translateToMouseGeneID(self.species, self.gene_id)
- traitList.append(thisTrait)
+ #XZ: As of Nov/13/2010, this dataset is 'UTHSC Illumina V6.2 RankInv B6 D2 average CNS GI average (May 08)'
+ self.tissue_probeset_freeze_id = 1
- if addLiteratureCorr:
- traitList = self.getLiteratureCorrelationByList(input_trait_mouse_geneid, species, traitList)
- if addTissueCorr:
- traitList = self.getTissueCorrelationByList( primaryTraitSymbol=input_trait_symbol, traitList=traitList,TissueProbeSetFreezeId =TissueProbeSetFreezeId, method=self.method)
+ traitList = self.correlate(vals)
+
+ _log.info("Done doing correlation calculation")
-########################################################
+############################################################################################################################################
TD_LR = HT.TD(height=200,width="100%",bgColor='#eeeeee')
mainfmName = webqtlUtil.genRandStr("fm_")
form = HT.Form(cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), enctype='multipart/form-data', name= mainfmName, submit=HT.Input(type='hidden'))
- hddn = {'FormID':'showDatabase', 'ProbeSetID':'_','database':self.target_db_name, 'databaseFull':self.db.fullname, 'CellID':'_', 'RISet':RISet, 'identification':fd.identification}
+ hddn = {'FormID': 'showDatabase',
+ 'ProbeSetID': '_',
+ 'database': self.target_db_name,
+ 'databaseFull': self.db.fullname,
+ 'CellID': '_',
+ 'RISet': fd.RISet,
+ 'identification': fd.identification}
if myTrait:
hddn['fullname']=fd.formdata.getvalue('fullname')
- if mdpchoice:
- hddn['MDPChoice']=mdpchoice
+ if mdp_choice:
+ hddn['MDPChoice']=mdp_choice
#XZ, 09/18/2008: pass the trait data to next page by hidden parameters.
@@ -510,13 +415,13 @@ class CorrelationPage(templatePage):
#XZ, 3/11/2010: add one parameter to record if the method is rank order.
form.append(HT.Input(name="rankOrder", value="%s" % rankOrder, type='hidden'))
- form.append(HT.Input(name="TissueProbeSetFreezeId", value="%s" % TissueProbeSetFreezeId, type='hidden'))
+ form.append(HT.Input(name="TissueProbeSetFreezeId", value="%s" % self.tissue_probeset_freeze_id, type='hidden'))
####################################
# generate the info on top of page #
####################################
- info = self.getTopInfo(myTrait=myTrait, method=self.method, db=self.db, target_db_name=self.target_db_name, returnNumber=self.returnNumber, methodDict=methodDict, totalTraits=totalTraits, identification=fd.identification )
+ info = self.getTopInfo(myTrait=myTrait, method=self.method, db=self.db, target_db_name=self.target_db_name, returnNumber=self.returnNumber, methodDict=self.CORRELATION_METHODS, totalTraits=traitList, identification=fd.identification )
##############
# Excel file #
@@ -536,7 +441,7 @@ class CorrelationPage(templatePage):
#####################################################################
-
+ #Select All, Deselect All, Invert Selection, Add to Collection
mintmap = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'showIntMap');" % mainfmName)
mintmap_img = HT.Image("/images/multiple_interval_mapping1_final.jpg", name='mintmap', alt="Multiple Interval Mapping", title="Multiple Interval Mapping", style="border:none;")
mintmap.append(mintmap_img)
@@ -555,10 +460,10 @@ class CorrelationPage(templatePage):
partialCorr = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'partialCorrInput');" % mainfmName)
partialCorr_img = HT.Image("/images/partial_correlation_final.jpg", name='partialCorr', alt="Partial Correlation", title="Partial Correlation", style="border:none;")
partialCorr.append(partialCorr_img)
- addselect = HT.Href(url="#redirect", onClick="addRmvSelection('%s', document.getElementsByName('%s')[0], 'addToSelection');" % (RISet, mainfmName))
+ addselect = HT.Href(url="#redirect", onClick="addRmvSelection('%s', document.getElementsByName('%s')[0], 'addToSelection');" % (fd.RISet, mainfmName))
addselect_img = HT.Image("/images/add_collection1_final.jpg", name="addselect", alt="Add To Collection", title="Add To Collection", style="border:none;")
addselect.append(addselect_img)
- selectall = HT.Href(url="#redirect", onClick="checkAll(document.getElementsByName('%s')[0]);" % mainfmName)
+ selectall = HT.Href(url="#redirect", onClick="checkAll(document.getElementsByName('%s')[0]);" % mainfmName)
selectall_img = HT.Image("/images/select_all2_final.jpg", name="selectall", alt="Select All", title="Select All", style="border:none;")
selectall.append(selectall_img)
selectinvert = HT.Href(url="#redirect", onClick = "checkInvert(document.getElementsByName('%s')[0]);" % mainfmName)
@@ -575,20 +480,90 @@ class CorrelationPage(templatePage):
selectandor.append(('OR','or'))
selectandor.selected.append('AND')
- pageTable = HT.TableLite(cellSpacing=0,cellPadding=0,width="100%", border=0, align="Left")
- containerTable = HT.TableLite(cellSpacing=0,cellPadding=0,width="90%",border=0, align="Left")
+ #External analysis tools
+ GCATButton = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'GCAT');" % mainfmName)
+ GCATButton_img = HT.Image("/images/GCAT_logo_final.jpg", name="GCAT", alt="GCAT", title="GCAT", style="border:none")
+ GCATButton.append(GCATButton_img)
+
+ ODE = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'ODE');" % mainfmName)
+ ODE_img = HT.Image("/images/ODE_logo_final.jpg", name="ode", alt="ODE", title="ODE", style="border:none")
+ ODE.append(ODE_img)
+
+ '''
+ #XZ, 07/07/2010: I comment out this block of code.
+ WebGestaltScript = HT.Script(language="Javascript")
+ WebGestaltScript.append("""
+setTimeout('openWebGestalt()', 2000);
+function openWebGestalt(){
+var thisForm = document['WebGestalt'];
+makeWebGestaltTree(thisForm, '%s', %d, 'edag_only.php');
+}
+ """ % (mainfmName, len(traitList)))
+ '''
+
+ self.cursor.execute('SELECT GeneChip.GO_tree_value FROM GeneChip, ProbeFreeze, ProbeSetFreeze WHERE GeneChip.Id = ProbeFreeze.ChipId and ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and ProbeSetFreeze.Name = "%s"' % self.db.name)
+ result = self.cursor.fetchone()
+
+ if result:
+ GO_tree_value = result[0]
+
+ if GO_tree_value:
+
+ WebGestalt = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'GOTree');" % mainfmName)
+ WebGestalt_img = HT.Image("/images/webgestalt_icon_final.jpg", name="webgestalt", alt="Gene Set Analysis Toolkit", title="Gene Set Analysis Toolkit", style="border:none")
+ WebGestalt.append(WebGestalt_img)
+
+ hddnWebGestalt = {
+ 'id_list':'',
+ 'correlation':'',
+ 'id_value':'',
+ 'llid_list':'',
+ 'id_type':GO_tree_value,
+ 'idtype':'',
+ 'species':'',
+ 'list':'',
+ 'client':''}
+
+ hddnWebGestalt['ref_type'] = hddnWebGestalt['id_type']
+ hddnWebGestalt['cat_type'] = 'GO'
+ hddnWebGestalt['significancelevel'] = 'Top10'
+
+ if self.species == 'rat':
+ hddnWebGestalt['org'] = 'Rattus norvegicus'
+ elif self.species == 'human':
+ hddnWebGestalt['org'] = 'Homo sapiens'
+ elif self.species == 'mouse':
+ hddnWebGestalt['org'] = 'Mus musculus'
+ else:
+ hddnWebGestalt['org'] = ''
+
+ for key in hddnWebGestalt.keys():
+ form.append(HT.Input(name=key, value=hddnWebGestalt[key], type='hidden'))
- optionsTable = HT.TableLite(cellSpacing=2, cellPadding=0,width="320", height="80", border=0, align="Left")
- optionsTable.append(HT.TR(HT.TD(selectall), HT.TD(reset), HT.TD(selectinvert), HT.TD(addselect), align="left"))
- optionsTable.append(HT.TR(HT.TD("&nbsp;"*1,"Select"), HT.TD("Deselect"), HT.TD("&nbsp;"*1,"Invert"), HT.TD("&nbsp;"*3,"Add")))
+
+ #Create tables with options, etc
+
+ pageTable = HT.TableLite(cellSpacing=0,cellPadding=0,width="100%", border=0, align="Left")
+
+ containerTable = HT.TableLite(cellSpacing=0,cellPadding=0,width="90%",border=0, align="Left")
+
+
+ if not GO_tree_value:
+ optionsTable = HT.TableLite(cellSpacing=2, cellPadding=0,width="480", height="80", border=0, align="Left")
+ optionsTable.append(HT.TR(HT.TD(selectall), HT.TD(reset), HT.TD(selectinvert), HT.TD(addselect), HT.TD(GCATButton), HT.TD(ODE), align="left"))
+ optionsTable.append(HT.TR(HT.TD("&nbsp;"*1,"Select"), HT.TD("Deselect"), HT.TD("&nbsp;"*1,"Invert"), HT.TD("&nbsp;"*3,"Add"), HT.TD("Gene Set"), HT.TD("&nbsp;"*2,"GCAT")))
+ else:
+ optionsTable = HT.TableLite(cellSpacing=2, cellPadding=0,width="560", height="80", border=0, align="Left")
+ optionsTable.append(HT.TR(HT.TD(selectall), HT.TD(reset), HT.TD(selectinvert), HT.TD(addselect), HT.TD(GCATButton), HT.TD(ODE), HT.TD(WebGestalt), align="left"))
+ optionsTable.append(HT.TR(HT.TD("&nbsp;"*1,"Select"), HT.TD("Deselect"), HT.TD("&nbsp;"*1,"Invert"), HT.TD("&nbsp;"*3,"Add"), HT.TD("Gene Set"), HT.TD("&nbsp;"*2,"GCAT"), HT.TD("&nbsp;"*3, "ODE")))
containerTable.append(HT.TR(HT.TD(optionsTable)))
functionTable = HT.TableLite(cellSpacing=2,cellPadding=0,width="480",height="80", border=0, align="Left")
functionRow = HT.TR(HT.TD(networkGraph, width="16.7%"), HT.TD(cormatrix, width="16.7%"), HT.TD(partialCorr, width="16.7%"), HT.TD(mcorr, width="16.7%"), HT.TD(mintmap, width="16.7%"), HT.TD(heatmap), align="left")
labelRow = HT.TR(HT.TD("&nbsp;"*1,HT.Text("Graph")), HT.TD("&nbsp;"*1,HT.Text("Matrix")), HT.TD("&nbsp;"*1,HT.Text("Partial")), HT.TD(HT.Text("Compare")), HT.TD(HT.Text("QTL Map")), HT.TD(HT.Text(text="Heat Map")))
functionTable.append(functionRow, labelRow)
- containerTable.append(HT.TR(HT.TD(functionTable), HT.BR()))
+ containerTable.append(HT.TR(HT.TD(functionTable), HT.BR()))
#more_options = HT.Image("/images/more_options1_final.jpg", name='more_options', alt="Expand Options", title="Expand Options", style="border:none;", Class="toggleShowHide")
@@ -597,12 +572,14 @@ class CorrelationPage(templatePage):
moreOptions = HT.Input(type='button',name='options',value='More Options', onClick="",Class="toggle")
fewerOptions = HT.Input(type='button',name='options',value='Fewer Options', onClick="",Class="toggle")
+ """
if (fd.formdata.getvalue('showHideOptions') == 'less'):
- containerTable.append(HT.TR(HT.TD("&nbsp;"), height="10"), HT.TR(HT.TD(HT.Div(fewerOptions, Class="toggleShowHide"))))
- containerTable.append(HT.TR(HT.TD("&nbsp;")))
+ containerTable.append(HT.TR(HT.TD("&nbsp;"), height="10"), HT.TR(HT.TD(HT.Div(fewerOptions, Class="toggleShowHide"))))
+ containerTable.append(HT.TR(HT.TD("&nbsp;")))
else:
- containerTable.append(HT.TR(HT.TD("&nbsp;"), height="10"), HT.TR(HT.TD(HT.Div(moreOptions, Class="toggleShowHide"))))
- containerTable.append(HT.TR(HT.TD("&nbsp;")))
+ containerTable.append(HT.TR(HT.TD("&nbsp;"), height="10"), HT.TR(HT.TD(HT.Div(moreOptions, Class="toggleShowHide"))))
+ containerTable.append(HT.TR(HT.TD("&nbsp;")))
+ """
containerTable.append(HT.TR(HT.TD(HT.Span(selecttraits,' with r > ',selectgt, ' ',selectandor, ' r < ',selectlt,Class="bd1 cbddf fs11")), style="display:none;", Class="extra_options"))
@@ -615,9 +592,9 @@ class CorrelationPage(templatePage):
if self.db.type=="Geno":
- containerTable.append(HT.TR(HT.TD(xlsUrl, height=40)))
+ containerTable.append(HT.TR(HT.TD(xlsUrl, height=40)))
- pageTable.append(HT.TR(HT.TD(containerTable)))
+ pageTable.append(HT.TR(HT.TD(containerTable)))
tblobj['header'], worksheet = self.getTableHeaderForGeno( method=self.method, worksheet=worksheet, newrow=newrow, headingStyle=headingStyle)
newrow += 1
@@ -636,9 +613,9 @@ class CorrelationPage(templatePage):
div = HT.Div(webqtlUtil.genTableObj(tblobj=tblobj, file=filename, sortby=sortby, tableID = "sortable", addIndex = "1"), corrScript, Id="sortable")
- pageTable.append(HT.TR(HT.TD(div)))
+ pageTable.append(HT.TR(HT.TD(div)))
- form.append(HT.Input(name='ShowStrains',type='hidden', value =1),
+ form.append(HT.Input(name='ShowStrains',type='hidden', value =1),
HT.Input(name='ShowLine',type='hidden', value =1),
HT.P(), HT.P(), pageTable)
TD_LR.append(corrHeading, info, form, HT.P())
@@ -649,9 +626,9 @@ class CorrelationPage(templatePage):
elif self.db.type=="Publish":
- containerTable.append(HT.TR(HT.TD(xlsUrl, height=40)))
+ containerTable.append(HT.TR(HT.TD(xlsUrl, height=40)))
- pageTable.append(HT.TR(HT.TD(containerTable)))
+ pageTable.append(HT.TR(HT.TD(containerTable)))
tblobj['header'], worksheet = self.getTableHeaderForPublish(method=self.method, worksheet=worksheet, newrow=newrow, headingStyle=headingStyle)
newrow += 1
@@ -661,7 +638,7 @@ class CorrelationPage(templatePage):
corrScript = HT.Script(language="Javascript")
corrScript.append("var corrArray = new Array();")
- tblobj['body'], worksheet, corrScript = self.getTableBodyForPublish(traitList=traitList, formName=mainfmName, worksheet=worksheet, newrow=newrow, corrScript=corrScript, species=species)
+ tblobj['body'], worksheet, corrScript = self.getTableBodyForPublish(traitList=traitList, formName=mainfmName, worksheet=worksheet, newrow=newrow, corrScript=corrScript, species=self.species)
workbook.close()
@@ -671,7 +648,7 @@ class CorrelationPage(templatePage):
# NL, 07/27/2010. genTableObj function has been moved from templatePage.py to webqtlUtil.py;
div = HT.Div(webqtlUtil.genTableObj(tblobj=tblobj, file=filename, sortby=sortby, tableID = "sortable", addIndex = "1"), corrScript, Id="sortable")
- pageTable.append(HT.TR(HT.TD(div)))
+ pageTable.append(HT.TR(HT.TD(div)))
form.append(
HT.Input(name='ShowStrains',type='hidden', value =1),
@@ -685,7 +662,6 @@ class CorrelationPage(templatePage):
elif self.db.type=="ProbeSet":
-
tblobj['header'], worksheet = self.getTableHeaderForProbeSet(method=self.method, worksheet=worksheet, newrow=newrow, headingStyle=headingStyle)
newrow += 1
@@ -694,7 +670,7 @@ class CorrelationPage(templatePage):
corrScript = HT.Script(language="Javascript")
corrScript.append("var corrArray = new Array();")
- tblobj['body'], worksheet, corrScript = self.getTableBodyForProbeSet(traitList=traitList, primaryTrait=myTrait, formName=mainfmName, worksheet=worksheet, newrow=newrow, corrScript=corrScript, species=species)
+ tblobj['body'], worksheet, corrScript = self.getTableBodyForProbeSet(traitList=traitList, primaryTrait=myTrait, formName=mainfmName, worksheet=worksheet, newrow=newrow, corrScript=corrScript, species=self.species)
workbook.close()
objfile = open('%s.obj' % (webqtlConfig.TMPDIR+filename), 'wb')
@@ -741,95 +717,21 @@ class CorrelationPage(templatePage):
#updated by NL. Delete function generateJavaScript, move js files to dhtml.js, webqtl.js and jqueryFunction.js
#variables: filename, strainIds and vals are required by getquerystring function
- strainIds=self.getStrainIds(species=species, strains=_strains)
+ strainIds=self.getStrainIds(species=self.species, strains=self.sample_names)
var1 = HT.Input(name="filename", value=filename, type='hidden')
var2 = HT.Input(name="strainIds", value=strainIds, type='hidden')
- var3 = HT.Input(name="vals", value=_vals, type='hidden')
+ var3 = HT.Input(name="vals", value=vals, type='hidden')
customizerButton = HT.Input(type="button", Class="button", value="Add Correlation", onClick = "xmlhttpPost('%smain.py?FormID=AJAX_table', 'sortable', (getquerystring(this.form)))" % webqtlConfig.CGIDIR)
containerTable.append(HT.TR(HT.TD(HT.Span(var1,var2,var3,customizerButton, "with", dbCustomizer, Class="bd1 cbddf fs11"), HT.BR(), HT.BR()), style="display:none;", Class="extra_options"))
- #outside analysis part
- GCATButton = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'GCAT');" % mainfmName)
- GCATButton_img = HT.Image("/images/GCAT_logo_final.jpg", name="GCAT", alt="GCAT", title="GCAT", style="border:none")
- GCATButton.append(GCATButton_img)
+ containerTable.append(HT.TR(HT.TD(xlsUrl, HT.BR(), HT.BR())))
- ODE = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'ODE');" % mainfmName)
- ODE_img = HT.Image("/images/ODE_logo_final.jpg", name="ode", alt="ODE", title="ODE", style="border:none")
- ODE.append(ODE_img)
+ pageTable.append(HT.TR(HT.TD(containerTable)))
- '''
- #XZ, 07/07/2010: I comment out this block of code.
- WebGestaltScript = HT.Script(language="Javascript")
- WebGestaltScript.append("""
-setTimeout('openWebGestalt()', 2000);
-function openWebGestalt(){
- var thisForm = document['WebGestalt'];
- makeWebGestaltTree(thisForm, '%s', %d, 'edag_only.php');
-}
- """ % (mainfmName, len(traitList)))
- '''
-
- self.cursor.execute('SELECT GeneChip.GO_tree_value FROM GeneChip, ProbeFreeze, ProbeSetFreeze WHERE GeneChip.Id = ProbeFreeze.ChipId and ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and ProbeSetFreeze.Name = "%s"' % self.db.name)
- result = self.cursor.fetchone()
+ pageTable.append(HT.TR(HT.TD(div)))
- if result:
- GO_tree_value = result[0]
-
- if GO_tree_value:
-
- WebGestalt = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'GOTree');" % mainfmName)
- WebGestalt_img = HT.Image("/images/webgestalt_icon_final.jpg", name="webgestalt", alt="Gene Set Analysis Toolkit", title="Gene Set Analysis Toolkit", style="border:none")
- WebGestalt.append(WebGestalt_img)
-
- hddnWebGestalt = {
- 'id_list':'',
- 'correlation':'',
- 'id_value':'',
- 'llid_list':'',
- 'id_type':GO_tree_value,
- 'idtype':'',
- 'species':'',
- 'list':'',
- 'client':''}
-
- hddnWebGestalt['ref_type'] = hddnWebGestalt['id_type']
- hddnWebGestalt['cat_type'] = 'GO'
- hddnWebGestalt['significancelevel'] = 'Top10'
-
- if species == 'rat':
- hddnWebGestalt['org'] = 'Rattus norvegicus'
- elif species == 'human':
- hddnWebGestalt['org'] = 'Homo sapiens'
- elif species == 'mouse':
- hddnWebGestalt['org'] = 'Mus musculus'
- else:
- hddnWebGestalt['org'] = ''
-
- for key in hddnWebGestalt.keys():
- form.append(HT.Input(name=key, value=hddnWebGestalt[key], type='hidden'))
-
-
- LinkOutTable = HT.TableLite(cellSpacing=2,cellPadding=0,width="320",height="80", border=0, align="Left")
-
- if not GO_tree_value:
- LinkOutRow = HT.TR(HT.TD(GCATButton, width="50%"), HT.TD(ODE, width="50%"), align="left")
- LinkOutLabels = HT.TR(HT.TD("&nbsp;", HT.Text("GCAT"), width="50%"), HT.TD("&nbsp;",HT.Text("ODE"), width="50%"), align="left")
- else:
- LinkOutRow = HT.TR(HT.TD(WebGestalt, width="25%"), HT.TD(GCATButton, width="25%"), HT.TD(ODE, width="25%"), align="left")
- LinkOutLabels = HT.TR(HT.TD(HT.Text("Gene Set")), HT.TD("&nbsp;"*2, HT.Text("GCAT")), HT.TD("&nbsp;"*3, HT.Text("ODE")), style="display:none;", Class="extra_options")
-
- LinkOutTable.append(LinkOutRow,LinkOutLabels)
-
- containerTable.append(HT.TR(HT.TD(LinkOutTable), Class="extra_options", style="display:none;"))
-
- containerTable.append(HT.TR(HT.TD(xlsUrl, HT.BR(), HT.BR())))
-
- pageTable.append(HT.TR(HT.TD(containerTable)))
-
- pageTable.append(HT.TR(HT.TD(div)))
-
- if species == 'human':
+ if self.species == 'human':
heatmap = ""
form.append(HT.Input(name='ShowStrains',type='hidden', value =1),
@@ -1009,7 +911,7 @@ Resorting this table <br>
tempTable = self.getTempLiteratureTable(species=species, input_species_geneid=GeneId, returnNumber=returnNumber)
if method == "4" or method == "5":
- tempTable = self.getTempTissueCorrTable(primaryTraitSymbol=GeneSymbol, TissueProbeSetFreezeId=tissueProbeSetFreezeId, method=method, returnNumber=returnNumber)
+ tempTable = self.getTempTissueCorrTable(primaryTraitSymbol=GeneSymbol, TissueProbeSetFreezeId=TISSUE_MOUSE_DB, method=method, returnNumber=returnNumber)
for step in range(nnn):
temp = []
@@ -1068,18 +970,30 @@ Resorting this table <br>
oridata.append(results)
datasize = len(oridata[0])
- traitdatabase = []
- # put all of the seperate data together into a huge list of lists
+ traits = []
+ # put all of the separate data together into a huge list of lists
for j in range(datasize):
traitdata = list(oridata[0][j])
for i in range(1,nnn):
traitdata += list(oridata[i][j][dataStartPos:])
- traitdatabase.append(traitdata)
+
+ trait = Trait(traitdata[0], traitdata[dataStartPos:])
+
+ if method == METHOD_LIT:
+ trait.lit_corr = traitdata[1]
+
+ if method in TISSUE_METHODS:
+ trait.tissue_corr = traitdata[1]
+ trait.p_tissue = traitdata[2]
+
+ traits.append(trait)
if tempTable:
self.cursor.execute( 'DROP TEMPORARY TABLE %s' % tempTable )
- return traitdatabase, dataStartPos
+ return traits
+
+
# XZ, 09/20/2008: This function creates TEMPORARY TABLE tmpTableName_2 and return its name.
@@ -1159,7 +1073,7 @@ Resorting this table <br>
except:
return 0
- symbolCorrDict, symbolPvalueDict = self.calculateCorrOfAllTissueTrait(primaryTraitSymbol=primaryTraitSymbol, TissueProbeSetFreezeId=TissueProbeSetFreezeId, method=method)
+ symbolCorrDict, symbolPvalueDict = self.calculateCorrOfAllTissueTrait(primaryTraitSymbol=primaryTraitSymbol, TissueProbeSetFreezeId=TISSUE_MOUSE_DB, method=method)
symbolCorrList = symbolCorrDict.items()
@@ -1216,7 +1130,7 @@ Resorting this table <br>
Returns a dictionary of 'TraitID':(tissueCorr, tissuePValue) for the requested correlation"""
- tempTable = self.getTempTissueCorrTable(primaryTraitSymbol=primaryTraitSymbol, TissueProbeSetFreezeId=TissueProbeSetFreezeId, method=method, returnNumber=returnNumber)
+ tempTable = self.getTempTissueCorrTable(primaryTraitSymbol=primaryTraitSymbol, TissueProbeSetFreezeId=TISSUE_MOUSE_DB, method=method, returnNumber=returnNumber)
query = "SELECT ProbeSet.Name, %s.Correlation, %s.PValue" % (tempTable, tempTable)
query += ' FROM (ProbeSet, ProbeSetXRef, ProbeSetFreeze)'
@@ -1276,6 +1190,225 @@ Resorting this table <br>
return traitList
+ def get_trait(self, cached, vals):
+
+ if cached:
+ _log.info("Using the fast method because the file exists")
+ lit_corrs = {}
+ tissue_corrs = {}
+ use_lit = False
+ if self.method == METHOD_LIT:
+ lit_corrs = self.fetchLitCorrelations(species=self.species, GeneId=self.gene_id, db=self.db, returnNumber=self.returnNumber)
+ use_lit = True
+
+ use_tissue_corr = False
+ if self.method in TISSUE_METHODS:
+ tissue_corrs = self.fetchTissueCorrelations(db=self.db, primaryTraitSymbol=self.trait_symbol, TissueProbeSetFreezeId=TISSUE_MOUSE_DB, method=self.method, returnNumber = self.returnNumber)
+ use_tissue_corr = True
+
+ DatabaseFileName = self.getFileName( target_db_name=self.target_db_name )
+ datasetFile = open(webqtlConfig.TEXTDIR+DatabaseFileName,'r')
+
+ #XZ, 01/08/2009: read the first line
+ line = datasetFile.readline()
+ cached_sample_names = webqtlUtil.readLineCSV(line)[1:]
+
+ #XZ, 01/08/2009: This step is critical. It is necessary for this new method.
+ #XZ: The original function fetchAllDatabaseData uses all strains stored in variable _strains to
+ #XZ: retrieve the values of each strain from database in real time.
+ #XZ: The new method uses all strains stored in variable dataset_strains to create a new variable
+ #XZ: _newvals. _newvals has the same length as dataset_strains. The items in _newvals is in
+ #XZ: the same order of items in dataset_strains. The value of each item in _newvals is either
+ #XZ: the value of correspinding strain in _vals or 'None'.
+ new_vals = []
+ for name in cached_sample_names:
+ if name in self.sample_names:
+ new_vals.append(float(vals[self.sample_names.index(name)]))
+ else:
+ new_vals.append('None')
+
+ nnCorr = len(new_vals)
+
+ #XZ, 01/14/2009: If literature corr or tissue corr is selected,
+ #XZ: there is no need to use parallel computing.
+
+ traits = []
+ data_start = 1
+ for line in datasetFile:
+ raw_trait = webqtlUtil.readLineCSV(line)
+ trait = Trait.from_csv(raw_trait, data_start)
+ trait.lit_corr = lit_corrs.get(trait.name)
+ trait.tissue_corr, trait.p_tissue = tissue_corrs.get(trait.name, (None, None))
+ traits.append(trait)
+
+ return traits, new_vals
+
+ else:
+ _log.info("Using the slow method for correlation")
+
+ _log.info("Fetching from database")
+ traits = self.fetchAllDatabaseData(species=self.species, GeneId=self.gene_id, GeneSymbol=self.trait_symbol, strains=self.sample_names, db=self.db, method=self.method, returnNumber=self.returnNumber, tissueProbeSetFreezeId= self.tissue_probeset_freeze_id)
+ _log.info("Done fetching from database")
+ totalTraits = len(traits) #XZ, 09/18/2008: total trait number
+
+ return traits, vals
+
+
+ def do_parallel_correlation(self):
+ _log.info("Invoking parallel computing")
+ input_line_list = datasetFile.readlines()
+ _log.info("Read lines from the file")
+ all_line_number = len(input_line_list)
+
+ step = 1000
+ job_number = math.ceil( float(all_line_number)/step )
+
+ job_input_lists = []
+
+ _log.info("Configuring jobs")
+
+ for job_index in range( int(job_number) ):
+ starti = job_index*step
+ endi = min((job_index+1)*step, all_line_number)
+
+ one_job_input_list = []
+
+ for i in range( starti, endi ):
+ one_job_input_list.append( input_line_list[i] )
+
+ job_input_lists.append( one_job_input_list )
+
+ _log.info("Creating pp servers")
+
+ ppservers = ()
+ # Creates jobserver with automatically detected number of workers
+ job_server = pp.Server(ppservers=ppservers)
+
+ _log.info("Done creating servers")
+
+ jobs = []
+ results = []
+
+ _log.info("Starting parallel computation, submitting jobs")
+ for one_job_input_list in job_input_lists: #pay attention to modules from outside
+ jobs.append( job_server.submit(func=compute_corr, args=(nnCorr, _newvals, one_job_input_list, self.method), depfuncs=(), modules=("utility.webqtlUtil",)) )
+ _log.info("Done submitting jobs")
+
+ for one_job in jobs:
+ one_result = one_job()
+ results.append( one_result )
+
+ _log.info("Acquiring results")
+
+ for one_result in results:
+ for one_traitinfo in one_result:
+ allcorrelations.append( one_traitinfo )
+
+ _log.info("Appending the results")
+
+ datasetFile.close()
+ totalTraits = len(allcorrelations)
+ _log.info("Done correlating using the fast method")
+
+
+ def correlate(self, vals):
+
+ correlations = []
+
+ #XZ: Use the fast method only for probeset dataset, and this dataset must have been created.
+ #XZ: Otherwise, use original method
+ _log.info("Entering correlation")
+
+ db_filename = self.getFileName( target_db_name=self.target_db_name )
+
+ cache_available = db_filename in os.listdir(webqtlConfig.TEXTDIR)
+
+ # If the cache file exists, do a cached correlation for probeset data
+ if self.db.type == "ProbeSet":
+# if self.method in [METHOD_SAMPLE_PEARSON, METHOD_SAMPLE_RANK] and cache_available:
+# traits = do_parallel_correlation()
+#
+# else:
+
+ (traits, vals) = self.get_trait(cache_available, vals)
+
+ for trait in traits:
+ trait.calculate_correlation(vals, self.method)
+
+ self.record_count = len(traits) #ZS: This isn't a good way to get this value, so I need to change it later
+
+ #XZ, 3/31/2010: Theoretically, we should create one function 'comTissueCorr'
+ #to compare each trait by their tissue corr p values.
+ #But because the tissue corr p values are generated by permutation test,
+ #the top ones always have p value 0. So comparing p values actually does nothing.
+ #In addition, for the tissue data in our database, the N is always the same.
+ #So it's safe to compare with tissue corr statistic value.
+ #That's the same as literature corr.
+ #if self.method in [METHOD_LIT, METHOD_TISSUE_PEARSON, METHOD_TISSUE_RANK] and self.gene_id:
+ # traits.sort(webqtlUtil.cmpLitCorr)
+ #else:
+ #if self.method in TISSUE_METHODS:
+ # sort(traits, key=lambda A: math.fabs(A.tissue_corr))
+ #elif self.method == METHOD_LIT:
+ # traits.sort(traits, key=lambda A: math.fabs(A.lit_corr))
+ #else:
+ traits = sortTraitCorrelations(traits, self.method)
+
+ # Strip to the top N correlations
+ traits = traits[:min(self.returnNumber, len(traits))]
+
+ addLiteratureCorr = False
+ addTissueCorr = False
+
+ trait_list = []
+ for trait in traits:
+ db_trait = webqtlTrait(db=self.db, name=trait.name, cursor=self.cursor)
+ db_trait.retrieveInfo( QTL='Yes' )
+
+ db_trait.Name = trait.name
+ db_trait.corr = trait.correlation
+ db_trait.nOverlap = trait.overlap
+ db_trait.corrPValue = trait.p_value
+
+ # NL, 07/19/2010
+ # js function changed, add a new parameter rankOrder for js function 'showTissueCorrPlot'
+ db_trait.RANK_ORDER = self.RANK_ORDERS[self.method]
+
+ #XZ, 26/09/2008: Method is 4 or 5. Have fetched tissue corr, but no literature correlation yet.
+ if self.method in TISSUE_METHODS:
+ db_trait.tissueCorr = trait.tissue_corr
+ db_trait.tissuePValue = trait.p_tissue
+ addTissueCorr = True
+
+
+ #XZ, 26/09/2008: Method is 3, Have fetched literature corr, but no tissue corr yet.
+ elif self.method == METHOD_LIT:
+ db_trait.LCorr = trait.lit_corr
+ db_trait.mouse_geneid = self.translateToMouseGeneID(self.species, db_trait.geneid)
+ addLiteratureCorr = True
+
+ #XZ, 26/09/2008: Method is 1 or 2. Have NOT fetched literature corr and tissue corr yet.
+ # Phenotype data will not have geneid, and neither will some probes
+ # we need to handle this because we will get an attribute error
+ else:
+ if self.input_trait_mouse_gene_id and self.db.type=="ProbeSet":
+ addLiteratureCorr = True
+ if self.trait_symbol and self.db.type=="ProbeSet":
+ addTissueCorr = True
+
+ trait_list.append(db_trait)
+
+ if addLiteratureCorr:
+ trait_list = self.getLiteratureCorrelationByList(self.input_trait_mouse_gene_id,
+ self.species, trait_list)
+ if addTissueCorr:
+ trait_list = self.getTissueCorrelationByList(
+ primaryTraitSymbol = self.trait_symbol,
+ traitList = trait_list,
+ TissueProbeSetFreezeId = TISSUE_MOUSE_DB,
+ method=self.method)
+
+ return trait_list
def calculateCorrOfAllTissueTrait(self, primaryTraitSymbol=None, TissueProbeSetFreezeId=None, method=None):
@@ -1283,10 +1416,10 @@ Resorting this table <br>
symbolCorrDict = {}
symbolPvalueDict = {}
- primaryTraitSymbolValueDict = correlationFunction.getGeneSymbolTissueValueDictForTrait(cursor=self.cursor, GeneNameLst=[primaryTraitSymbol], TissueProbeSetFreezeId=TissueProbeSetFreezeId)
+ primaryTraitSymbolValueDict = correlationFunction.getGeneSymbolTissueValueDictForTrait(cursor=self.cursor, GeneNameLst=[primaryTraitSymbol], TissueProbeSetFreezeId=TISSUE_MOUSE_DB)
primaryTraitValue = primaryTraitSymbolValueDict.values()[0]
- SymbolValueDict = correlationFunction.getGeneSymbolTissueValueDictForTrait(cursor=self.cursor, GeneNameLst=[], TissueProbeSetFreezeId=TissueProbeSetFreezeId)
+ SymbolValueDict = correlationFunction.getGeneSymbolTissueValueDictForTrait(cursor=self.cursor, GeneNameLst=[], TissueProbeSetFreezeId=TISSUE_MOUSE_DB)
if method in ["2","5"]:
symbolCorrDict, symbolPvalueDict = correlationFunction.batchCalTissueCorr(primaryTraitValue,SymbolValueDict,method='spearman')
@@ -1301,7 +1434,7 @@ Resorting this table <br>
#XZ, 10/13/2010
def getTissueCorrelationByList(self, primaryTraitSymbol=None, traitList=None, TissueProbeSetFreezeId=None, method=None):
- primaryTraitSymbolValueDict = correlationFunction.getGeneSymbolTissueValueDictForTrait(cursor=self.cursor, GeneNameLst=[primaryTraitSymbol], TissueProbeSetFreezeId=TissueProbeSetFreezeId)
+ primaryTraitSymbolValueDict = correlationFunction.getGeneSymbolTissueValueDictForTrait(cursor=self.cursor, GeneNameLst=[primaryTraitSymbol], TissueProbeSetFreezeId=TISSUE_MOUSE_DB)
if primaryTraitSymbol.lower() in primaryTraitSymbolValueDict:
primaryTraitValue = primaryTraitSymbolValueDict[primaryTraitSymbol.lower()]
@@ -1312,7 +1445,7 @@ Resorting this table <br>
if hasattr(thisTrait, 'symbol'):
geneSymbolList.append(thisTrait.symbol)
- SymbolValueDict = correlationFunction.getGeneSymbolTissueValueDictForTrait(cursor=self.cursor, GeneNameLst=geneSymbolList, TissueProbeSetFreezeId=TissueProbeSetFreezeId)
+ SymbolValueDict = correlationFunction.getGeneSymbolTissueValueDictForTrait(cursor=self.cursor, GeneNameLst=geneSymbolList, TissueProbeSetFreezeId=TISSUE_MOUSE_DB)
for thisTrait in traitList:
if hasattr(thisTrait, 'symbol') and thisTrait.symbol and thisTrait.symbol.lower() in SymbolValueDict:
@@ -1339,7 +1472,7 @@ Resorting this table <br>
if myTrait:
if method in ["1","2"]: #genetic correlation
info = HT.Paragraph("Values of Record %s in the " % myTrait.getGivenName(), HT.Href(text=myTrait.db.fullname,url=webqtlConfig.INFOPAGEHREF % myTrait.db.name,target="_blank", Class="fwn"),
- " database were compared to all %d records in the " % totalTraits, HT.Href(text=db.fullname,url=webqtlConfig.INFOPAGEHREF % target_db_name,target="_blank", Class="fwn"),
+ " database were compared to all %d records in the " % self.record_count, HT.Href(text=db.fullname,url=webqtlConfig.INFOPAGEHREF % target_db_name,target="_blank", Class="fwn"),
' database. The top %d correlations ranked by the %s are displayed.' % (returnNumber,methodDict[method]),
' You can resort this list using the small arrowheads in the top row.')
else:
@@ -1359,7 +1492,7 @@ Resorting this table <br>
' You can resort this list using the small arrowheads in the top row.' )
elif identification:
- info = HT.Paragraph('Values of %s were compared to all %d traits in ' % (identification, totalTraits),
+ info = HT.Paragraph('Values of %s were compared to all %d traits in ' % (identification, self.record_count),
HT.Href(text=db.fullname,url=webqtlConfig.INFOPAGEHREF % target_db_name,target="_blank",Class="fwn"),
' database. The TOP %d correlations ranked by the %s are displayed.' % (returnNumber,methodDict[method]),
' You can resort this list using the small arrowheads in the top row.')
@@ -1934,7 +2067,7 @@ Resorting this table <br>
TCorr = thisTrait.tissueCorr
TCorrStr = "%2.3f" % thisTrait.tissueCorr
# NL, 07/19/2010: add a new parameter rankOrder for js function 'showTissueCorrPlot'
- rankOrder = thisTrait.rankOrder
+ rankOrder = self.RANK_ORDERS[self.method]
TCorrPlotURL = "javascript:showTissueCorrPlot('%s','%s','%s',%d)" %(formName, primaryTrait.symbol, thisTrait.symbol,rankOrder)
tr.append(TDCell(HT.TD(HT.Href(text=TCorrStr, url=TCorrPlotURL, Class="fs12 fwn ff1"), Class="fs12 fwn ff1 b1 c222", align='right'), TCorrStr, abs(TCorr)))
else: