Removed everything from 'web' directory except genofiles and renamed the directory to 'genotype_files'

5 files changed, 0 insertions, 1479 deletions

diff --git a/web/webqtl/correlationMatrix/CorrelationMatrixPage.py b/web/webqtl/correlationMatrix/CorrelationMatrixPage.py
deleted file mode 100755
index a01111f5..00000000
--- a/web/webqtl/correlationMatrix/CorrelationMatrixPage.py
+++ /dev/null
@@ -1,595 +0,0 @@
-# Copyright (C) University of Tennessee Health Science Center, Memphis, TN.
-#
-# This program is free software: you can redistribute it and/or modify it
-# under the terms of the GNU Affero General Public License
-# as published by the Free Software Foundation, either version 3 of the
-# License, or (at your option) any later version.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
-# See the GNU Affero General Public License for more details.
-#
-# This program is available from Source Forge: at GeneNetwork Project
-# (sourceforge.net/projects/genenetwork/).
-#
-# Contact Drs. Robert W. Williams and Xiaodong Zhou (2010)
-# at rwilliams@uthsc.edu and xzhou15@uthsc.edu
-#
-#
-#
-# This module is used by GeneNetwork project (www.genenetwork.org)
-#
-# Created by GeneNetwork Core Team 2010/08/10
-#
-# Last updated by NL 2011/02/14
-
-import os
-import string
-from htmlgen import HTMLgen2 as HT
-import sys
-import time
-import numarray
-import numarray.linear_algebra as la
-import piddle as pid
-import math
-
-from base.templatePage import templatePage
-from base import webqtlConfig
-from base.webqtlTrait import webqtlTrait
-from utility import webqtlUtil
-from utility import Plot
-
-
-
-# XZ, 09/09/2008: After adding several traits to collection, click "Correlation Matrix" button,
-# XZ, 09/09/2008: This class will generate what you see.
-#########################################
-#      Correlation Matrix Page
-#########################################
-
-class CorrelationMatrixPage(templatePage):
-
-    def __init__(self,fd,InputData=None):
-
-        templatePage.__init__(self, fd)
-
-        self.dict['title'] = 'Correlation Matrix'
-
-        if not self.openMysql():
-            return
-            
-        if not fd.genotype:
-            fd.readGenotype()
-            fd.strainlist = fd.f1list + fd.strainlist
-            
-        #self.searchResult = fd.formdata.getvalue('searchResult')
-        self.oldSearchResult = fd.formdata.getvalue('oldSearchResult')
-        
-        if self.oldSearchResult:
-            try:
-                self.searchResult = fd.formdata.getvalue('oldSearchResult')
-            except:
-            	self.searchResult = fd.formdata.getvalue('searchResult')
-        
-        else:
-        	self.searchResult = fd.formdata.getvalue('searchResult')
-        
-        if not self.searchResult:
-            heading = 'Correlation Matrix'
-            detail = ['You need to select at least two traits in order to generate correlation matrix.']
-            self.error(heading=heading,detail=detail)
-            return
-        if type("1") == type(self.searchResult):
-            self.searchResult = [self.searchResult]
-        
-        if self.searchResult:
-            #testvals,names,dbInfos = self.getAllSearchResult(fd,self.searchResult)
-            if len(self.searchResult) > webqtlConfig.MAXCORR:
-                heading = 'Correlation Matrix'
-                detail = ['In order to display Correlation Matrix properly, Do not select more than %d traits for Correlation Matrix.' % webqtlConfig.MAXCORR]
-                self.error(heading=heading,detail=detail)
-                return
-
-            #XZ, 7/22/2009: this block is not necessary
-            #elif len(self.searchResult) > 40:
-            #    noPCA = 1
-            #else:
-            #    noPCA = 0
-    
-            traitList = []
-            traitDataList = []
-            for item in self.searchResult:
-                thisTrait = webqtlTrait(fullname=item, cursor=self.cursor)
-                thisTrait.retrieveInfo()
-                thisTrait.retrieveData(fd.strainlist)
-                traitList.append(thisTrait)
-                traitDataList.append(thisTrait.exportData(fd.strainlist))
-                
-        else:
-            heading = 'Correlation Matrix'
-            detail = [HT.Font('Error : ',color='red'),HT.Font('Error occurs while retrieving data FROM database.',color='black')]
-            self.error(heading=heading,detail=detail)
-            return
-
-        NNN = len(traitList)
-        
-        if NNN == 0:
-            heading = "Correlation Matrix"
-            detail = ['No trait was selected for %s data set. No matrix generated.' % self.data.RISet]
-            self.error(heading=heading,detail=detail)
-            return
-        elif NNN < 2:
-            heading = 'Correlation Matrix'
-            detail = ['You need to select at least two traits in order to generate correlation matrix.']
-            self.error(heading=heading,detail=detail)
-            return
-        else:
-        	
-        	
-        	
-            corArray = [([0] * (NNN+1))[:] for i in range(NNN+1)]
-            pearsonArray = [([0] * (NNN))[:] for i in range(NNN)]
-            spearmanArray = [([0] * (NNN))[:] for i in range(NNN)]
-            corArray[0][0] = 'Correlation'
-            TD_LR = HT.TD(colspan=2,width="100%",bgColor='#eeeeee')
-            form = HT.Form( cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), enctype='multipart/form-data', name='showDatabase', submit=HT.Input(type='hidden'))
-            hddn = {'FormID':'showDatabase', 'ProbeSetID':'_','database':'_',
-            'CellID':'_','ProbeSetID2':'_','database2':'_','CellID2':'_',
-            'newNames':fd.formdata.getvalue("newNames", "_"), 
-            'RISet':fd.RISet,'ShowStrains':'ON','ShowLine':'ON', 'rankOrder':'_', 
-            "allstrainlist":string.join(fd.strainlist, " "), 'traitList':string.join(self.searchResult, "\t")}
-            if fd.incparentsf1:
-                hddn['incparentsf1']='ON'
-            	    
-            for key in hddn.keys():
-                form.append(HT.Input(name=key, value=hddn[key], type='hidden'))
-           
-            for item in self.searchResult:
-            	form.append(HT.Input(name='oldSearchResult', value=str(item), type='hidden'))
-            
-            traiturls = []
-            traiturls2 = []
-            shortNames = []
-            verboseNames = []
-            verboseNames2 = []
-            verboseNames3 = []
-            abbreviation = ''
-            
-            #dbInfo.ProbeSetID = ProbeSetID
-            #dbInfo.CellID = CellID
-            for i, thisTrait in enumerate(traitList):
-                _url = "javascript:showDatabase2('%s','%s','%s');" % (thisTrait.db.name, thisTrait.name, thisTrait.cellid)
-                #_text = 'Trait%d: ' % (i+1)+str(thisTrait)
-                _text = 'Trait %d: ' % (i+1)+thisTrait.displayName()
-                                
-                if thisTrait.db.type == 'Geno':
-                    _shortName = 'Genotype'
-                    abbreviation = 'Genotype'
-                    _verboseName = 'Locus %s' % (thisTrait.name)
-                    _verboseName2 = 'Chr %s @ %s Mb' % (thisTrait.chr, '%2.3f' % thisTrait.mb)
-                    _verboseName3 = ''
-                elif thisTrait.db.type == 'Publish':
-                    if thisTrait.post_publication_abbreviation:
-                        AbbreviationString = thisTrait.post_publication_abbreviation
-                    else:
-                        AbbreviationString = ''
-                    if thisTrait.confidential:
-                        if not webqtlUtil.hasAccessToConfidentialPhenotypeTrait(privilege=self.privilege, userName=self.userName, authorized_users=thisTrait.authorized_users):
-                            if thisTrait.pre_publication_abbreviation:
-                                AbbreviationString = thisTrait.pre_publication_abbreviation
-                            else:
-                                AbbreviationString = ''
-                    _shortName = 'Phenotype: %s' % (AbbreviationString)  
-                    _verboseName2 = ''
-                    _verboseName3 = ''
-                    if thisTrait.pubmed_id:
-                        _verboseName = 'PubMed %d: ' % thisTrait.pubmed_id
-                    else: 
-                        _verboseName = 'Unpublished '
-                    _verboseName += 'RecordID/%s' % (thisTrait.name)
-                    PhenotypeString = thisTrait.post_publication_description
-                    if thisTrait.confidential:
-                        if not webqtlUtil.hasAccessToConfidentialPhenotypeTrait(privilege=self.privilege, userName=self.userName, authorized_users=thisTrait.authorized_users):
-                            PhenotypeString = thisTrait.pre_publication_description
-                    _verboseName2 = 'Phenotype: %s' % (PhenotypeString)
-                    if thisTrait.authors:
-                        a1 = string.split(thisTrait.authors,',')[0]
-                        while a1[0] == '"' or a1[0] == "'" :
-                            a1 = a1[1:]
-                            _verboseName += ' by '
-                            _verboseName += HT.Italic('%s, and colleagues' % (a1))
-                elif thisTrait.db.type == 'Temp':
-                    abbreviation = ''
-                    _shortName = thisTrait.name
-                    if thisTrait.description:
-                        _verboseName = thisTrait.description
-                    else:
-                        _verboseName = 'Temp'
-                    _verboseName2 = ''
-                    _verboseName3 = ''
-                else:
-                    abbreviation = thisTrait.symbol
-                    _shortName = 'Symbol: %s ' % thisTrait.symbol
-                    _verboseName = thisTrait.symbol
-                    _verboseName2 = ''
-                    _verboseName3 = ''
-                    if thisTrait.chr and thisTrait.mb:
-                        _verboseName += ' on Chr %s @ %s Mb' % (thisTrait.chr,thisTrait.mb)
-                    if thisTrait.description:
-                        _verboseName2 = '%s' % (thisTrait.description)
-                    if thisTrait.probe_target_description:
-                        _verboseName3 = '%s' % (thisTrait.probe_target_description)         
-                                
-                cururl = HT.Href(text=_text, url=_url,Class='fs12') 
-                cururl2 = HT.Href(text='Trait%d' % (i+1),url=_url,Class='fs12')
-                traiturls.append(cururl)
-                traiturls2.append(cururl2)
-                shortName = HT.Div(id="shortName_" + str(i), style="display:none")
-                shortName.append(_shortName)
-                shortNames.append(shortName)
-                verboseName = HT.Div(id="verboseName_" + str(i), style="display:none")
-                verboseName.append(_verboseName)
-                verboseNames.append(verboseName)
-                verboseName2 = HT.Div(id="verboseName2_" + str(i), style="display:none")
-                verboseName2.append(_verboseName2)
-                verboseNames2.append(verboseName2)
-                verboseName3 = HT.Div(id="verboseName3_" + str(i), style="display:none")
-                verboseName3.append(_verboseName3)
-                verboseNames3.append(verboseName3)
-                    
-
-                                
-                corArray[i+1][0] = 'Trait%d: ' % (i+1)+str(thisTrait) + '/' + str(thisTrait) + ': ' + abbreviation + '/' + str(thisTrait) + ': ' + str(_verboseName) + ' : ' + str(_verboseName2) + ' : ' + str(_verboseName3)
-                corArray[0][i+1] = 'Trait%d: ' % (i+1)+str(thisTrait)
-                
-            corMatrixHeading = HT.Paragraph('Correlation Matrix', Class="title")
-            
-            tbl = HT.TableLite(Class="collap", border=0, cellspacing=1, 
-                cellpadding=5, width='100%')
-            row1 = HT.TR(HT.TD(Class="fs14 fwb ffl b1 cw cbrb"),
-                HT.TD('Spearman Rank Correlation (rho)', Class="fs14 fwb ffl b1 cw cbrb", colspan= NNN+1,align="center")
-                )
-            row2 = HT.TR(
-                HT.TD("P e a r s o n &nbsp;&nbsp;&nbsp; r", rowspan= NNN+1,Class="fs14 fwb ffl b1 cw cbrb", width=10,align="center"),
-                HT.TD(Class="b1", width=300))
-            for i in range(NNN):
-                row2.append(HT.TD(traiturls2[i], Class="b1", align="center"))
-            tbl.append(row1,row2)
-
-            nOverlapTrait =9999            
-            nnCorr = len(fd.strainlist)
-            for i, thisTrait in enumerate(traitList):
-                newrow = HT.TR()
-                newrow.append(HT.TD(traiturls[i], shortNames[i], verboseNames[i], verboseNames2[i], 
-                                    verboseNames3[i], Class="b1"))
-                names1 = [thisTrait.db.name, thisTrait.name, thisTrait.cellid]
-                for j, thisTrait2 in enumerate(traitList):
-                    names2 = [thisTrait2.db.name, thisTrait2.name, thisTrait2.cellid]
-                    if j < i:
-                        corr,nOverlap = webqtlUtil.calCorrelation(traitDataList[i],traitDataList[j],nnCorr)
-                        
-                        rank = fd.formdata.getvalue("rankOrder", "0")
-                        
-                        if nOverlap < nOverlapTrait:
-                            nOverlapTrait = nOverlap
-                        if corr > 0.7:
-                            fontcolor="red"
-                        elif corr > 0.5:
-                            fontcolor="#FF6600"
-                        elif corr < -0.7:
-                            fontcolor="blue"
-                        elif corr < -0.5:
-                            fontcolor="#009900"
-                        else:
-                            fontcolor ="#000000"
-
-                        pearsonArray[i][j] = corr
-                        pearsonArray[j][i] = corr
-                        if corr!= 0.0:
-                            corArray[i+1][j+1] = '%2.3f/%d' % (corr,nOverlap)
-                            thisurl = HT.Href(text=HT.Font('%2.3f'% corr,HT.BR(),'%d' % nOverlap ,color=fontcolor, Class="fs11 fwn"),url = "javascript:showCorrelationPlot2(db='%s',ProbeSetID='%s',CellID='%s',db2='%s',ProbeSetID2='%s',CellID2='%s',rank='%s')" % (names1[0], names1[1], names1[2], names2[0], names2[1], names2[2], rank))
-                        else:
-                            corArray[i+1][j+1] = '---/%d' % nOverlap
-                            thisurl = HT.Font('---',HT.BR(), '%d' % nOverlap)
-                        
-                        newrow.append(HT.TD(thisurl,Class="b1",NOWRAP="ON",align="middle"))
-                    elif j == i:
-                        corr,nOverlap = webqtlUtil.calCorrelation(traitDataList[i],traitDataList[j],nnCorr)
-                        pearsonArray[i][j] = 1.0
-                        spearmanArray[i][j] = 1.0
-                        corArray[i+1][j+1] = '%2.3f/%d' % (corr,nOverlap)
-                        nOverlap = webqtlUtil.calCorrelation(traitDataList[i],traitDataList[j],nnCorr)[1]
-                        newrow.append(HT.TD(HT.Href(text=HT.Font(HT.Italic("n"),HT.BR(),str(nOverlap),Class="fs11 fwn b1",align="center", color="000000"), url="javascript:showDatabase2('%s','%s','%s')" % (thisTrait.db.name, thisTrait.name, thisTrait.cellid)), bgColor='#cccccc', align="center", Class="b1", NOWRAP="ON"))
-                    else:       
-                        corr,nOverlap = webqtlUtil.calCorrelationRank(traitDataList[i],traitDataList[j],nnCorr)
-                        
-                        rank = fd.formdata.getvalue("rankOrder", "1")
-                        
-                        if corr > 0.7:
-                            fontcolor="red"
-                        elif corr > 0.5:
-                            fontcolor="#FF6600"
-                        elif corr < -0.7:
-                            fontcolor="blue"
-                        elif corr < -0.5:
-                            fontcolor="#009900"
-                        else:
-                            fontcolor ="#000000"
-                        spearmanArray[i][j] = corr
-                        spearmanArray[j][i] = corr
-                        if corr!= 0.0:
-                            corArray[i+1][j+1] = '%2.3f/%d' % (corr,nOverlap)
-                            thisurl = HT.Href(text=HT.Font('%2.3f'% corr,HT.BR(),'%d' % nOverlap ,color=fontcolor, Class="fs11 fwn"),url = "javascript:showCorrelationPlot2(db='%s',ProbeSetID='%s',CellID='%s',db2='%s',ProbeSetID2='%s',CellID2='%s',rank='%s')" % (names1[0], names1[1], names1[2], names2[0], names2[1], names2[2], rank))
-                        else:
-                            corArray[i+1][j+1] = '---/%d' % nOverlap
-                            thisurl = HT.Span('---',HT.BR(), '%d' % nOverlap, Class="fs11 fwn")
-                        newrow.append(HT.TD(thisurl,Class="b1", NOWRAP="ON",align="middle"))
-                tbl.append(newrow)
-                
-            info = HT.Blockquote('Lower left cells list Pearson product-moment correlations; upper right cells list Spearman rank order correlations. Each cell also contains the n of cases. Values higher than 0.7 are displayed in ',HT.Font('red', color='red'),'; those between 0.5 and 0.7 in  ',HT.Font('orange', color='#FF6600'),'; Values lower than -0.7 are in ',HT.Font('blue', color='blue'),'; between -0.5 and -0.7 in ',HT.Font('green', color='#009900'),'. Select any cell to generate a scatter plot. Select trait labels for more information.', Class="fs13 fwn")
-            
-            exportbutton = HT.Input(type='button',  name='export', value='Export', onClick="exportText(allCorrelations);",Class="button")
-            shortButton = HT.Input(type='button' ,name='dispShort',value=' Short Labels ', onClick="displayShortName();",Class="button")
-            verboseButton = HT.Input(type='button' ,name='dispVerbose',value=' Long Labels ', onClick="displayVerboseName();", Class="button")
-            form.append(HT.Blockquote(tbl,HT.P(),shortButton,verboseButton,exportbutton))
-            TD_LR.append(corMatrixHeading,info,form,HT.P())
-
-            #if noPCA:
-            #    TD_LR.append(HT.Blockquote('No PCA is computed if more than 32 traits are selected.'))
-
-            #print corArray
-            exportScript = """
-                <SCRIPT language=JavaScript>
-                var allCorrelations = %s;
-                </SCRIPT>
-
-            """
-            exportScript = exportScript % str(corArray)
-            self.dict['js1'] = exportScript+'<SCRIPT SRC="/javascript/correlationMatrix.js"></SCRIPT><BR>'
-            self.dict['body'] = str(TD_LR)
-            
-            #don't calculate PCA while number exceed 32
-            #if noPCA:
-            #    return
-
-            #XZ, 7/22/2009: deal with PCA stuff
-            #Only for Array Data
-            
-            if NNN > 2:
-    
-                traitname = map(lambda X:str(X.name), traitList)
-                
-                #generate eigenvalues
-                
-                # import sys
-                sys.argv=[" "]
-                # import numarray
-                # import numarray.linear_algebra as la
-                #spearmanEigen = eigenvectors(array(spearmanArray))
-                pearsonEigen = la.eigenvectors(numarray.array(pearsonArray))
-                #spearmanEigenValue,spearmanEigenVectors = self.sortEigenVectors(spearmanEigen)
-                pearsonEigenValue,pearsonEigenVectors = self.sortEigenVectors(pearsonEigen)
-		
-				
-		"""
-		for i in range(len(pearsonEigenValue)):
-			if type(pearsonEigenValue[i]).__name__ == 'complex':
-				pearsonEigenValue[i] = pearsonEigenValue[i].real
-		for i in range(len(pearsonEigenVectors)):
-			for j in range(len(pearsonEigenVectors[i])):
-				if type(pearsonEigenVectors[i][j]).__name__ == 'complex':
-					pearsonEigenVectors[i][j] = pearsonEigenVectors[i][j].real
-				if type(pearsonEigenVectors[i][j]).__name__ == 'complex':
-					pearsonEigenVectors[i][j] = pearsonEigenVectors[i][j].real		      
-		"""
-        
-		if type(pearsonEigenValue[0]).__name__ == 'complex':
-		   pass
-		else:	
-            	   traitHeading = HT.Paragraph('PCA Traits',align='left', Class="title")  
-                   
-        	   tbl2 = self.calcPCATraits(traitDataList=traitDataList, nnCorr=nnCorr, NNN=NNN, pearsonEigenValue=pearsonEigenValue, 
-                                         pearsonEigenVectors=pearsonEigenVectors, form=form, fd=fd)
-                   #Buttons on search page
-                   #mintmap = HT.Input(type='button' ,name='mintmap',value='Multiple Mapping', onClick="databaseFunc(this.form,'showIntMap');",Class="button")
-                   addselect = HT.Input(type='button' ,name='addselect',value='Add to Collection', onClick="addRmvSelection('%s', this.form, 'addToSelection');"  % fd.RISet,Class="button")
-                   selectall = HT.Input(type='button' ,name='selectall',value='Select All', onClick="checkAll(this.form);",Class="button")
-                   reset = HT.Input(type='reset',name='',value='Select None',Class="button")
-                   updateNames = HT.Input(type='button', name='updateNames',value='Update Trait Names', onClick="editPCAName(this.form);", Class="button")
-                   chrMenu = HT.Input(type='hidden',name='chromosomes',value='all')
-                   
-                   """
-                   #need to be refined
-                   if fd.genotype.Mbmap:
-                       scaleMenu = HT.Select(name='scale')
-                       scaleMenu.append(tuple(["Genetic Map",'morgan']))
-                       scaleMenu.append(tuple(["Physical Map",'physic']))
-                   else:
-                       scaleMenu = ""
-                   """    
-                   
-                   tbl2.append(HT.TR(HT.TD(HT.P(),chrMenu,updateNames,selectall,reset,addselect,colspan=3)))
-        	   form.append(HT.P(),traitHeading,HT.Blockquote(tbl2))
-                
-                   plotHeading1 = HT.Paragraph('Scree Plot', Class="title") 
-                   TD_LR.append(plotHeading1)
-                   img1 = self.screePlot(NNN=NNN, pearsonEigenValue=pearsonEigenValue)
-    
-                   TD_LR.append(HT.Blockquote(img1))
-                   
-                   plotHeading2 = HT.Paragraph('Factor Loadings Plot', Class="title")
-                   TD_LR.append(plotHeading2)
-                   img2 = self.factorLoadingsPlot(pearsonEigenVectors=pearsonEigenVectors, traitList=traitList)
-                   
-                   TD_LR.append(HT.Blockquote(img2))                      
-
-        self.dict['body'] = str(TD_LR)
-    
-    def screePlot(self, NNN=0, pearsonEigenValue=None):
-
-        c1 = pid.PILCanvas(size=(700,500))
-        Plot.plotXY(canvas=c1, dataX=range(1,NNN+1), dataY=pearsonEigenValue, rank=0, labelColor=pid.blue,plotColor=pid.red, symbolColor=pid.blue, XLabel='Factor Number', connectdot=1,YLabel='Percent of Total Variance %', title='Pearson\'s R Scree Plot')
-        filename= webqtlUtil.genRandStr("Scree_")
-        c1.save(webqtlConfig.IMGDIR+filename, format='gif')
-        img=HT.Image('/image/'+filename+'.gif',border=0)
-        
-        return img
-    
-    def factorLoadingsPlot(self, pearsonEigenVectors=None, traitList=None):
-        
-        traitname = map(lambda X:str(X.name), traitList)
-        c2 = pid.PILCanvas(size=(700,500))
-        Plot.plotXY(c2, pearsonEigenVectors[0],pearsonEigenVectors[1], 0, dataLabel = traitname, labelColor=pid.blue, plotColor=pid.red, symbolColor=pid.blue,XLabel='Factor (1)', connectdot=1, YLabel='Factor (2)', title='Factor Loadings Plot (Pearson)', loadingPlot=1)
-        filename= webqtlUtil.genRandStr("FacL_")
-        c2.save(webqtlConfig.IMGDIR+filename, format='gif')
-        img = HT.Image('/image/'+filename+'.gif',border=0)
-     
-        return img
-    
-    def calcPCATraits(self, traitDataList=None, nnCorr=0, NNN=0, pearsonEigenValue=None, pearsonEigenVectors=None, form=None, fd=None):  
-       """
-       This function currently returns the html to be displayed instead of the traits themselves. Need to fix later.
-       """
-    
-       detailInfo = string.split(self.searchResult[0],':')
-    
-       self.sameProbeSet = 'yes'
-       for item in self.searchResult[1:]:
-           detailInfo2 = string.split(item,':')
-           if detailInfo[0] != detailInfo2[0] or detailInfo[1] != detailInfo2[1]:
-               self.sameProbeSet = None
-               break
-                
-       for item in traitDataList:
-           if len(item) != nnCorr:
-               return
-       infoStrains = []
-       infoStrainsPos = []
-       dataArray  = [[] for i in range(NNN)]
-    
-       for i in range(len(traitDataList[0])):
-           currentStrain = 1
-           for j in range(NNN):
-               if not traitDataList[j][i]:
-                   currentStrain = 0
-                   break
-           if currentStrain == 1:
-               infoStrains.append(fd.strainlist[i])
-               infoStrainsPos.append(i)
-               for j in range(NNN): 
-                   dataArray[j].append(traitDataList[j][i])
-
-    
-       self.cursor.execute('delete Temp, TempData FROM Temp, TempData WHERE Temp.DataId = TempData.Id and UNIX_TIMESTAMP()-UNIX_TIMESTAMP(CreateTime)>%d;' % webqtlConfig.MAXLIFE)
-
-       StrainIds = []
-       for item in infoStrains:
-           self.cursor.execute('SELECT Strain.Id FROM Strain,StrainXRef, InbredSet WHERE Strain.Name="%s" and Strain.Id = StrainXRef.StrainId and StrainXRef.InbredSetId = InbredSet.Id and InbredSet.Name = "%s"' % (item, fd.RISet))
-           StrainIds.append('%d' % self.cursor.fetchone()[0])
-    
-       """
-       #minimal 12 overlapping strains      
-       if len(dataArray[0]) < 12:
-           form.append(HT.P(),traitHeading,HT.Blockquote(HT.Paragraph('The number of overlapping strains is less than 12, no PCA scores computed.',align='left')))
-           self.dict['body'] = str(TD_LR)
-           return
-       """
-       dataArray = self.zScore(dataArray)
-       dataArray = numarray.array(dataArray)
-       dataArray2 = numarray.dot(pearsonEigenVectors,dataArray)
-    
-       tbl2 = HT.TableLite(cellSpacing=2,cellPadding=0,border=0, width="100%")
-    
-       ct0 = time.localtime(time.time())
-       ct = time.strftime("%B/%d %H:%M:%S",ct0)
-       if self.sameProbeSet:
-           newDescription = 'PCA Traits generated at %s from %s' % (ct,detailInfo[1])
-       else:
-           newDescription = 'PCA Traits generated at %s from traits selected' % ct
-    
-
-       j = 1
-       self.cursor.execute('SELECT Id  FROM InbredSet WHERE Name = "%s"' % fd.RISet)
-       InbredSetId = self.cursor.fetchall()[0][0]
-       user_ip = fd.remote_ip
-       if fd.formdata.getvalue("newNames"):
-           newNames = fd.formdata.getvalue("newNames").split(",")
-       else:
-       	   newNames = 0
-       
-       for item in dataArray2:
-           if pearsonEigenValue[j-1] < 100.0/NNN:
-               break
-           
-           if (newNames == 0):
-               description  = '%s : PC%02d' % (newDescription, j)              
-           else:    
-               description = '%s : %s' % (newDescription, newNames[j-1])           	   
-                  
-           self.cursor.execute('SELECT max(id) FROM TempData')
-           try:
-               DataId = self.cursor.fetchall()[0][0] + 1
-           except:
-               DataId = 1
-           newProbeSetID = webqtlUtil.genRandStr("PCA_Tmp_")
-           self.cursor.execute('insert into Temp(Name,description, createtime,DataId,InbredSetId,IP) values(%s,%s,Now(),%s,%s,%s)' ,(newProbeSetID, description, DataId,InbredSetId,user_ip))
-        
-           k = 0    
-           for StrainId in StrainIds:
-               self.cursor.execute('insert into TempData(Id, StrainId, value) values(%s,%s,%s)' % (DataId, StrainId, item[k]*(-1.0)))
-               k += 1
-           setDescription = HT.Div(id="pcaTrait%s" % j)
-           descriptionLink = HT.Href(text=description, url="javascript:showDatabase2('Temp','%s','')" % newProbeSetID, Class="fwn")
-           descriptionEdit = HT.Input(type='text', value='', name='editName%s' % j)
-           
-           #onBlur='editPDAName(this.form, %s);' % j
-           
-           setDescription.append(descriptionLink)
-           setDescription.append(descriptionEdit)
-           
-           traitName = "%s:%s" % ('Temp',newProbeSetID)
-           tbl2.append(HT.TR(HT.TD("%d."%j,align="right",valign="top"),HT.TD(HT.Input(type="checkbox", Class="checkbox", name="searchResult",value=traitName),valign="top",width=50),HT.TD(setDescription)))
-           j += 1
-    
-       return tbl2
-    
-    def zScore(self,dataArray):
-        NN = len(dataArray[0])
-        if NN < 10:
-            return dataArray
-        else:
-            i = 0
-            for data in dataArray:
-                N = len(data)
-                S = reduce(lambda x,y: x+y, data, 0.)
-                SS = reduce(lambda x,y: x+y*y, data, 0.)
-                mean = S/N
-                var = SS - S*S/N
-                stdev = math.sqrt(var/(N-1))
-                data2 = map(lambda x:(x-mean)/stdev,data)
-                dataArray[i] = data2
-                i += 1
-            return dataArray
-    
-    def sortEigenVectors(self,vector):
-        try:
-            eigenValues = vector[0].tolist()
-            eigenVectors = vector[1].tolist()
-            combines = []
-            i = 0
-            for item in eigenValues:
-                combines.append([eigenValues[i],eigenVectors[i]])
-                i += 1
-            combines.sort(webqtlUtil.cmpEigenValue)
-            A = []
-            B = []
-            for item in combines:
-                A.append(item[0])
-                B.append(item[1])
-            sum = reduce(lambda x,y: x+y, A, 0.0)
-            A = map(lambda x:x*100.0/sum, A) 
-            return [A,B]
-        except:
-            return []
-
diff --git a/web/webqtl/correlationMatrix/TissueAbbreviationPage.py b/web/webqtl/correlationMatrix/TissueAbbreviationPage.py
deleted file mode 100755
index ad8f0ac7..00000000
--- a/web/webqtl/correlationMatrix/TissueAbbreviationPage.py
+++ /dev/null
@@ -1,79 +0,0 @@
-# Copyright (C) University of Tennessee Health Science Center, Memphis, TN.
-#
-# This program is free software: you can redistribute it and/or modify it
-# under the terms of the GNU Affero General Public License
-# as published by the Free Software Foundation, either version 3 of the
-# License, or (at your option) any later version.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
-# See the GNU Affero General Public License for more details.
-#
-# This program is available from Source Forge: at GeneNetwork Project
-# (sourceforge.net/projects/genenetwork/).
-#
-# Contact Drs. Robert W. Williams and Xiaodong Zhou (2010)
-# at rwilliams@uthsc.edu and xzhou15@uthsc.edu
-#
-#
-#
-# This module is used by GeneNetwork project (www.genenetwork.org)
-#
-# Created by GeneNetwork Core Team 2011/12/7
-#
-# Last updated by GeneNetwork Core Team 2011/12/7
-
-
-from base.templatePage import templatePage
-from htmlgen import HTMLgen2 as HT
-
-import string
-import os
-
-
-class TissueAbbreviationPage (templatePage):
-
-    def __init__(self,fd):
-		templatePage.__init__(self, fd)
-		
-		shortName=fd.formdata.getfirst("shortTissueName", ',')
-		fullName=fd.formdata.getfirst("fullTissueName", ',')
-		shortNameList=[]
-		fullNameList=[]
-		
-		if shortName:
-			shortNameList=shortName.split(',')
-			
-		if fullName:
-			fullNameList=fullName.split(',')
-			
-		tissueAbbrDict={}
-		for i, item in enumerate(shortNameList):
-			tissueAbbrDict[item]=fullNameList[i]	
-			
-		if tissueAbbrDict:
-		
-			# Creates the table for the fullname and shortname of Tissue
-			tissueAbbrTable = HT.TableLite(border=1, cellspacing=5, cellpadding=3, Class="collap")
-			shortNameList = tissueAbbrDict.keys()
-			shortNameList.sort()
-			abbrHeaderStyle="fs14 fwb ffl"
-			abbrStyle="fs14 fwn ffl"
-			
-			tissueAbbrTable.append(HT.TR(HT.TD('Abbr&nbsp;&nbsp;', Class=abbrHeaderStyle, NOWRAP = 1),HT.TD('Full Name&nbsp;&nbsp;', Class=abbrHeaderStyle, NOWRAP = 1)))
-			for item in shortNameList:
-				thisTR = HT.TR(HT.TD(item, Class=abbrStyle, NOWRAP = 1))
-				thisTR.append(HT.TD(tissueAbbrDict[item], Class=abbrStyle, NOWRAP = 1))
-
-				tissueAbbrTable.append(thisTR)
-				
-			self.dict['body'] = HT.TD(HT.Paragraph("Tissue Abbreviation", Class="title"), HT.Blockquote(tissueAbbrTable))
-			self.dict['title'] = "Tissue Abbreviation" 
-		else:
-			heading = "Tissue abbreviation"
-			detail = ["Cannot found Tissue Abbreviation. Please try again later."]
-			self.error(heading=heading,detail=detail)
-			return			
-           
-
diff --git a/web/webqtl/correlationMatrix/TissueCorrelationPage.py b/web/webqtl/correlationMatrix/TissueCorrelationPage.py
deleted file mode 100755
index 7cb86d8c..00000000
--- a/web/webqtl/correlationMatrix/TissueCorrelationPage.py
+++ /dev/null
@@ -1,673 +0,0 @@
-# Copyright (C) University of Tennessee Health Science Center, Memphis, TN.
-#
-# This program is free software: you can redistribute it and/or modify it
-# under the terms of the GNU Affero General Public License
-# as published by the Free Software Foundation, either version 3 of the
-# License, or (at your option) any later version.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
-# See the GNU Affero General Public License for more details.
-#
-# This program is available from Source Forge: at GeneNetwork Project
-# (sourceforge.net/projects/genenetwork/).
-#
-# Contact Drs. Robert W. Williams and Xiaodong Zhou (2010)
-# at rwilliams@uthsc.edu and xzhou15@uthsc.edu
-#
-#
-#
-# This module is used by GeneNetwork project (www.genenetwork.org)
-# user can search correlation value and P-Value by inputting one pair gene symbols or multiple gene symbols.
-
-# Created by GeneNetwork Core Team 2010/07/07
-# Last updated by NL, 2011/03/25
-
-from htmlgen import HTMLgen2 as HT
-import os
-import sys
-import time
-import string
-import pyXLWriter as xl
-import cPickle
-
-from base.templatePage import templatePage
-from base import webqtlConfig
-from base.webqtlTrait import webqtlTrait
-from correlationMatrix.tissueCorrelationMatrix import tissueCorrelationMatrix
-from utility import webqtlUtil
-from utility.THCell import THCell
-from utility.TDCell import TDCell
-
-
-#########################################
-#      Tissue Correlation Page
-#########################################
-
-class  TissueCorrelationPage(templatePage):
-
-	def __init__(self, fd):
-
-		templatePage.__init__(self, fd)
-				
-		if not self.openMysql():
-			return	
-		
-		#read input fields
-		self.action = fd.formdata.getvalue("action", "").strip()
-		self.geneSymbols = fd.formdata.getvalue("geneSymbols","").strip()
-		self.tissueProbeSetFeezeId = fd.formdata.getvalue("tissueProbeSetFeezeId", "").strip()
-		self.recordReturnNum = fd.formdata.getvalue("recordReturnNum", "0").strip()
-		self.calculateMethod = fd.formdata.getvalue("calculateMethod", "0").strip()
-		
-		TissueCorrMatrixObject = tissueCorrelationMatrix(tissueProbeSetFreezeId=self.tissueProbeSetFeezeId)
-		
-		if not self.geneSymbols:	
-			# default page 
-			
-			Heading = HT.Paragraph("Tissue Correlation", Class="title")
-			Intro = HT.Blockquote("This function computes correlations between transcript expression across different organs and tissues.")
-			Intro.append(HT.BR(),"Select a data set from the pull-down menu and then compute correlations.")
-
-			formName='searchTissueCorrelation'
-			form = HT.Form(cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), target='_blank',enctype='multipart/form-data', name= formName, submit=HT.Input(type='hidden'))
-			form.append(HT.Input(type="hidden", name="FormID", value=""))
-			form.append(HT.Input(type="hidden", name="action", value="disp"))
-			
-			# added by NL 10/12/2010, retreive dataSet info from TissueProbeSetFreeze to get all TissueProbeSetFreezeId, datasetName and FullName
-			tissProbeSetFreezeIds,dataSetNames,dataSetfullNames = TissueCorrMatrixObject.getTissueDataSet()
-
-			dataSetList=[]
-			for i in range(len(tissProbeSetFreezeIds)):
-				dataSetList.append((dataSetfullNames[i], tissProbeSetFreezeIds[i]))
-			dataSetMenu = HT.Select(dataSetList,name="tissueProbeSetFeezeId")
-
-			InfoFile =HT.Input(type="button", Class="button", value=" Info ", onClick="tissueDatasetInfo(this.form.tissueProbeSetFeezeId,%s);"%(dataSetNames))	
-			form.append(HT.Strong("&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;"),dataSetMenu,InfoFile,HT.BR());
-			
-			form.append(HT.BR(),HT.Strong("&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Please enter only one gene symbol/ENTREZ gene Id per line."),HT.BR(),HT.Strong("&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;"),HT.Textarea(name="geneSymbols", rows=10, cols=50, text=""),HT.BR(),HT.BR())				
-			# calculate method radio button
-			calculateMethodMenu =HT.Input(type="radio", name="calculateMethod", value="0", checked="checked")
-			calculateMethodMenu1 =HT.Input(type="radio", name="calculateMethod", value="1")
-			# record Return method dropdown menu
-			recordReturnMenu = HT.Select(name="recordReturnNum")
-			recordReturnMenu.append(('Top 100','0'))
-			recordReturnMenu.append(('Top 200','1'))
-			recordReturnMenu.append(('Top 500','2'))
-			recordReturnMenu.append(('Top 1000','3'))
-			recordReturnMenu.append(('Top 2000','4'))
-			recordReturnMenu.append(('All','5'))	
-			
-			# working for input symbol has only one; 
-			form.append(HT.Strong("&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;"),HT.Span("Return:", Class="ffl fwb fs12"),HT.Strong("&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;"),recordReturnMenu,HT.BR());
-			form.append(HT.BR(),HT.Strong("&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;"),'Pearson',calculateMethodMenu,"&nbsp;"*3,'Spearman Rank',calculateMethodMenu1,HT.BR(),HT.BR());
-			form.append(HT.Strong("&nbsp;&nbsp;&nbsp;"),HT.Input(type="button", value="&nbsp;Compute&nbsp;", Class="button",onClick="selectFormIdForTissueCorr('%s');"%formName))
-			form.append(HT.Strong("&nbsp;&nbsp;&nbsp;&nbsp;"),HT.Input(type="button", Class="button", value="&nbsp;Make Default&nbsp;", onClick = "makeTissueCorrDefault(this.form);"))
-
-			TD_LR = HT.TD(height=200,width="100%",bgcolor='#eeeeee',align="left")		
-			TD_LR.append(Heading,Intro,form)
-			self.content_type = 'text/html'
-			self.dict['js1'] = '<SCRIPT SRC="/javascript/correlationMatrix.js"></SCRIPT><BR>'
-			# get tissueProbesetFreezeId from cookie
-			self.dict['js2'] = 'onload ="getTissueCorrDefault(\'searchTissueCorrelation\');"'
-			self.dict['body'] = str(TD_LR)
-			self.dict['title'] = "Tissue Correlation"
-		elif self.action == 'disp':
-			TissueCount =TissueCorrMatrixObject.getTissueCountofCurrentDataset()
-	
-			# add by NL for first Note part in the tissue correlation page. 2010-12-23
-			note =""
-			dataSetName=""
-			datasetFullName=""
-			dataSetName, datasetFullName= TissueCorrMatrixObject.getFullnameofCurrentDataset()
-
-			noteURL = "../dbdoc/"+ dataSetName+".html"
-			noteText = " was used to compute expression correlation across %s samples of tissues and organs.&nbsp["%TissueCount			
-			# dataset download
-			datasetURL = "../dbdoc/"+ dataSetName+".xls"
-			datasetDownload =HT.Href(text="Download experiment data",url=datasetURL,Class='fs13',target="_blank")
-			note = HT.Blockquote(HT.Href(text=datasetFullName,url=noteURL,Class='fs13',target="_blank"),noteText, datasetDownload,"]",HT.BR())
-			
-			geneSymbolLst = [] # gene Symbol list
-			geneSymbolLst = TissueCorrMatrixObject.getGeneSymbolLst(self.geneSymbols)
-			
-			symbolCount = len(geneSymbolLst)			
-			# The input symbol limit is 100.
-			heading = "Tissue Correlation" 
-			if symbolCount > 100:
-				detail = ['The Gene symbols you have input are more than 100. Please limit them to 100.'] 
-				self.error(heading=heading,detail=detail)
-				return		
-			elif symbolCount==0:
-				detail = ['No Gene Symbol was input. No Tissue Correlation matrix generated.' ]
-				self.error(heading=heading,detail=detail)
-				return
-			else:
-				# search result page
-				# The input symbols should be no less than 1.				
-				self.content_type = 'text/html'				
-				if symbolCount == 1:	
-					self.displaySingleSymbolResultPage(primaryGeneSymbol=geneSymbolLst[0],datasetFullName=datasetFullName,tProbeSetFreezeId=self.tissueProbeSetFeezeId, TissueCorrMatrixObject =TissueCorrMatrixObject,recordReturnNum=self.recordReturnNum,method=self.calculateMethod, note=note,TissueCount =TissueCount)			
-				else:	
-					self.displayMultiSymbolsResultPage(geneSymbolLst=geneSymbolLst, symbolCount=symbolCount, tProbeSetFreezeId=self.tissueProbeSetFeezeId,TissueCorrMatrixObject =TissueCorrMatrixObject,note=note,TissueCount =TissueCount)
-
-		else:
-			heading = "Tissue Correlation"
-			detail = ['There\'s something wrong with input gene symbol(s), or the value of parameter [action] is not right.' ]
-			self.error(heading=heading,detail=detail)
-			return
-#############################
-# functions
-#############################
-
-	# result page when input symbol has only one
-	def displaySingleSymbolResultPage(self,primaryGeneSymbol=None, datasetFullName=None,tProbeSetFreezeId=None, TissueCorrMatrixObject =None,recordReturnNum=None,method=None,note=None,TissueCount =None):
-		formName = webqtlUtil.genRandStr("fm_")
-		form = HT.Form(cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), enctype='multipart/form-data',name= formName, submit=HT.Input(type='hidden'))
-		# the following hidden elements are required parameter in Class(PlotCorrelationPage). So we need to define them here. 
-		form.append(HT.Input(type="hidden", name="action", value="disp"))
-		form.append(HT.Input(type="hidden", name="FormID", value="dispSingleTissueCorrelation"))
-		form.append(HT.Input(type="hidden", name="X_geneSymbol", value=""))
-		form.append(HT.Input(type="hidden", name="Y_geneSymbol", value=""))
-		form.append(HT.Input(type="hidden", name="ProbeSetID", value=""))
-		# RISet is not using in Tissue correlation, but is a required parameter in Class(PlotCorrelationPage). So we set dummy value(BXD). 
-		form.append(HT.Input(type="hidden", name="RISet", value="BXD"))
-		form.append(HT.Input(type="hidden", name="ShowLine", value="1"))
-		form.append(HT.Input(type="hidden", name="TissueProbeSetFreezeId", value=tProbeSetFreezeId))
-		form.append(HT.Input(type="hidden", name="rankOrder", value=0))	
-		
-		traitList =[]
-		try:
-			symbolCorrDict, symbolPvalueDict = TissueCorrMatrixObject.calculateCorrOfAllTissueTrait(primaryTraitSymbol=primaryGeneSymbol,method=method)
-		except:
-			heading = "Tissue Correlation"
-			detail = ['Please use the official NCBI gene symbol.' ]
-			self.error(heading=heading,detail=detail)			
-			return
-		
-		symbolList0,geneIdDict,dataIdDict,ChrDict,MbDict,descDict,pTargetDescDict=TissueCorrMatrixObject.getTissueProbeSetXRefInfo(GeneNameLst=[])					
-		# In case, upper case and lower case issue of symbol, mappedByTargetList function will update input geneSymbolLst based on database search result
-		tempPrimaryGeneSymbol =self.mappedByTargetList(primaryList=symbolList0,targetList=[primaryGeneSymbol])
-		primaryGeneSymbol =tempPrimaryGeneSymbol[0]
-		
-		returnNum = self.getReturnNum(recordReturnNum)
-		symbolListSorted=[]
-		symbolList=[]
-		# get key(list) of symbolCorrDict(dict) based on sorting symbolCorrDict(dict) by its' value in desc order
-		symbolListSorted=sorted(symbolCorrDict, key=symbolCorrDict.get, reverse=True)
-		symbolList = self.mappedByTargetList(primaryList=symbolList0,targetList=symbolListSorted)
-		
-		if returnNum==None:
-			returnNum =len(symbolList0)
-			IntroReturnNum ="All %d "%returnNum
-		else:
-			IntroReturnNum ="The Top %d" %returnNum
-			
-		symbolList = symbolList[:returnNum]
-
-		pageTable = HT.TableLite(cellSpacing=0,cellPadding=0,width="100%", border=0, align="Left")
-		
-		##############
-		# Excel file #
-		##############
-		filename= webqtlUtil.genRandStr("Corr_")								
-		xlsUrl = HT.Input(type='button', value = 'Download Table', onClick= "location.href='/tmp/%s.xls'" % filename, Class='button')
-		# Create a new Excel workbook
-		workbook = xl.Writer('%s.xls' % (webqtlConfig.TMPDIR+filename))
-		headingStyle = workbook.add_format(align = 'center', bold = 1, border = 1, size=13, fg_color = 0x1E, color="white")
-		#There are 6 lines of header in this file. 
-		worksheet = self.createExcelFileWithTitleAndFooter(workbook=workbook, datasetName=datasetFullName, returnNumber=returnNum)
-		newrow = 6				
-		pageTable.append(HT.TR(HT.TD(xlsUrl,height=40)))
-		
-		# get header part of result table and export excel file
-		tblobj = {}
-		tblobj['header'], worksheet = self.getTableHeader( method=method, worksheet=worksheet, newrow=newrow, headingStyle=headingStyle)
-		newrow += 1
-
-		# get body part of result table and export excel file
-		tblobj['body'], worksheet = self.getTableBody(symbolCorrDict=symbolCorrDict, symbolPvalueDict=symbolPvalueDict,symbolList=symbolList,geneIdDict=geneIdDict,ChrDict=ChrDict,MbDict=MbDict,descDict=descDict,pTargetDescDict=pTargetDescDict,primarySymbol=primaryGeneSymbol,TissueCount=TissueCount, formName=formName, worksheet=worksheet, newrow=newrow,method=method)
-		workbook.close()
-		# creat object for result table for sort function
-		objfile = open('%s.obj' % (webqtlConfig.TMPDIR+filename), 'wb')
-		cPickle.dump(tblobj, objfile)
-		objfile.close()	
-
-		sortby = ("tissuecorr", "down")
-		div = HT.Div(webqtlUtil.genTableObj(tblobj=tblobj, file=filename, sortby=sortby, tableID = "sortable", addIndex = "1"), Id="sortable")								
-		
-		if method =="0":
-			IntroMethod="Pearson\'s r "
-		else:
-			IntroMethod="Spearman\'s rho "				
-		Intro = HT.Blockquote('%s correlations ranked by the %s are displayed.' % (IntroReturnNum,IntroMethod),
-				' You can resort this list using the small arrowheads in the top row.')	
-		Intro.append(HT.BR(),' Click the correlation values to generate scatter plots. Select the symbol to open NCBI Entrez.')
-				
-		pageTable.append(HT.TR(HT.TD(div)))
-		form.append(HT.P(), HT.P(),pageTable)
-		corrHeading = HT.Paragraph('Tissue Correlation Table', Class="title")
-		TD_LR = HT.TD(height=200,width="100%",bgcolor='#eeeeee',align="left")
-		TD_LR.append(corrHeading,note,Intro, form, HT.P())
-
-		self.dict['body'] =  str(TD_LR)
-		self.dict['js1'] = '<SCRIPT SRC="/javascript/correlationMatrix.js"></SCRIPT><BR>'
-		self.dict['title'] = 'Tissue Correlation Result'						
-	
-		return
-
-	# result page when input symbols are more than 1	
-	def displayMultiSymbolsResultPage(self, geneSymbolLst=None, symbolCount=None, tProbeSetFreezeId=None,TissueCorrMatrixObject=None,note=None,TissueCount =None):
-		
-		formName = webqtlUtil.genRandStr("fm_")
-		form = HT.Form(cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), enctype='multipart/form-data',name= formName, submit=HT.Input(type='hidden'))
-		# the following hidden elements are required parameter in Class(PlotCorrelationPage). So we need to define them here. 
-		form.append(HT.Input(type="hidden", name="action", value="disp"))
-		form.append(HT.Input(type="hidden", name="FormID", value="dispMultiTissueCorrelation"))
-		form.append(HT.Input(type="hidden", name="X_geneSymbol", value=""))
-		form.append(HT.Input(type="hidden", name="Y_geneSymbol", value=""))
-		form.append(HT.Input(type="hidden", name="ProbeSetID", value=""))
-		# RISet is not using in Tissue correlation, but is a required parameter in Class(PlotCorrelationPage). So we set dummy value(BXD). 
-		form.append(HT.Input(type="hidden", name="RISet", value="BXD"))
-		form.append(HT.Input(type="hidden", name="ShowLine", value="1"))
-		form.append(HT.Input(type="hidden", name="TissueProbeSetFreezeId", value=tProbeSetFreezeId))
-		form.append(HT.Input(type="hidden", name="rankOrder", value=0))			
-
-		# updated by NL, 2011-01-06, build multi list for later use to descrease access to db again
-		symbolList,geneIdDict,dataIdDict,ChrDict,MbDict,descDict,pTargetDescDict = TissueCorrMatrixObject.getTissueProbeSetXRefInfo(GeneNameLst=geneSymbolLst)
-		# In case, upper case and lower case issue of symbol, mappedByTargetList function will update input geneSymbolLst based on database search result
-		geneSymbolLst =self.mappedByTargetList(primaryList=symbolList,targetList=geneSymbolLst)
-		
-		# Added by NL, 2011-01-06, get all shortNames, verboseNames, verboseNames2, verboseNames3, exportArray 
-		# for Short Label, Long Label, Export functions			
-		geneIdLst,shortNames, verboseNames, verboseNames2, verboseNames3, exportArray = self.getAllLabelsInfo(geneSymbolList =geneSymbolLst, geneIdDict=geneIdDict,ChrDict=ChrDict, MbDict=MbDict, descDict=descDict, pTargetDescDict=pTargetDescDict)
-	
-		heading = "Tissue Correlation Matrix" 
-		
-		#get correlation value and p value based on Gene Symbols list, and return the values in corrArray and pvArray seperately 
-		corrArray,pvArray = TissueCorrMatrixObject.getTissueCorrPvArray(geneNameLst=geneSymbolLst,dataIdDict=dataIdDict)
-
-		# in the matrix table, top right corner displays Spearman Rank Correlation's Values and P-Values for each pair of geneSymbols; 
-		#                      left bottom displays Pearson Correlation values and P-Vlues for each pair of geneSymbols.
-		tissueCorrMatrixHeading = HT.Paragraph(heading,Class="title")
-		tcmTable = HT.TableLite(Class="collap", border=0, cellspacing=1, cellpadding=5, width='100%')	
-		row1 = HT.TR(HT.TD(Class="fs14 fwb ffl b1 cw cbrb"),HT.TD('Spearman Rank Correlation (rho)' , Class="fs14 fwb ffl b1 cw cbrb", colspan= symbolCount+2,align="center"))
-		col1 = HT.TR(HT.TD("P e a r s o n &nbsp;&nbsp;&nbsp; r", rowspan= symbolCount+1,Class="fs14 fwb ffl b1 cw cbrb", width=10,align="center"),HT.TD("Gene Symbol",Class="fs13 fwb cb b1", width=300))
-		for i in range(symbolCount):
-			GeneSymbol=geneSymbolLst[i].strip()
-			geneId = geneIdLst[i]
-
-			if geneId!=0:
-				_url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene&cmd=Retrieve&dopt=Graphics&list_uids=%s" % geneId
-				curURL = HT.Href(text=GeneSymbol,url=_url,Class='fs13',target="_blank")
-			else:
-				curURL = GeneSymbol
-			col1.append(HT.TD(curURL,Class="b1", align="center"))				
-
-		tcmTable.append(row1,col1)
-		# to decide to whether to show note for "*" or not
-		flag = 0
-		for i in range(symbolCount):
-			GeneSymbol=geneSymbolLst[i].strip()  
-			geneId = geneIdLst[i]
-			
-			newrow = HT.TR()
-			newrow.append(HT.Input(name="Symbol", value=GeneSymbol, type='hidden'))
-
-			if geneId!=0:
-				_url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene&cmd=Retrieve&dopt=Graphics&list_uids=%s" %geneId
-				geneIdURL = HT.Href(text="%s "%GeneSymbol,url=_url,Class="b1",target="_blank")
-			else:
-				# flag =1 will show note for "*"
-				flag = 1
-				geneIdURL =HT.Italic("%s"%GeneSymbol,HT.Font('*', color='red'))				
-			newrow.append(HT.TD(geneIdURL,shortNames[i],verboseNames[i],verboseNames2[i],verboseNames3[i], Class="b1", align="left",NOWRAP="ON"))
-
-			for j in range(symbolCount):
-				GeneSymbol2=geneSymbolLst[j].strip() 
-				corr = corrArray[i][j]
-				pValue = pvArray[i][j]
-				Color=''
-
-				if j==i:
-					newrow.append(HT.TD(HT.Font(HT.Italic("n"),HT.BR(),str(TissueCount),Class="fs11 fwn b1",align="center", color="000000"), bgColor='#cccccc', align="center", Class="b1", NOWRAP="ON"))
-					exportArray[i+1][j+1] = '%d/%d' % (TissueCount,TissueCount)
-				else:
-					if corr:
-						corr = float(corr)
-						tCorr = "%2.3f" % corr
-						pValue = float(pValue)
-						tPV = "%2.3f" % pValue
-
-						# updated by NL, based on Rob's requirement: delete p value, 2010-02-14	
-						# set color for cells by correlationValue
-						if corr > 0.7:
-							fontcolor="red"
-						elif corr > 0.5:
-							fontcolor="#FF6600"
-						elif corr < -0.7:
-							fontcolor="blue"
-						elif corr < -0.5:
-							fontcolor="#009900"
-						else:
-							fontcolor ="#000000"
-							
-						# set label for cells
-						# if rank is equal to 0, pearson correlation plot will be the first one; 
-						# if rank is equal to 1, spearman ran correlation plot will be the first one.
-						if j>i:				
-							exportArray[i+1][j+1] =tCorr+"/"+tPV
-							rank =1
-						elif j<i:
-							exportArray[i+1][j+1] =tCorr+"/"+tPV
-							rank =0
-						
-						tCorrStr= tCorr
-						tPVStr = tPV 
-						tCorrPlotURL = "javascript:showTissueCorrPlot('%s','%s','%s',%d)" %(formName,GeneSymbol, GeneSymbol2,rank) 					
-						corrURL= HT.Href(text=HT.Font(tCorrStr,HT.BR(),color=fontcolor, Class="fs11 fwn"), url = tCorrPlotURL)						
-					else:
-						corr = 'N/A'
-						corrURL= HT.Font(corr)
-						exportArray[i+1][j+1] ="---/---"
-						
-					newrow.append(HT.TD(corrURL,bgColor=Color,Class="b1",NOWRAP="ON",align="middle"))
-
-			tcmTable.append(newrow)
-
-										
-		
-		Intro = HT.Blockquote('Lower left cells list Pearson ',HT.EM('r'),' values; upper right cells list Spearman rho values. Each cell also contains the n samples of tissues and organs. Values higher than 0.7 are displayed in ',HT.Font('red', color='red'),'; those between 0.5 and 0.7 in  ',HT.Font('orange', color='#FF6600'),'; Values lower than -0.7 are in ',HT.Font('blue', color='blue'),'; between -0.5 and -0.7 in ',HT.Font('green', color='#009900'),'.', HT.BR(),HT.BR(), HT.Strong('Make scatter plots by clicking on cell values '),'(', HT.EM('r'),' or rho). ', Class="fs13 fwn")
-        		
-		shortButton = HT.Input(type='button' ,name='dispShort',value=' Short Labels ', onClick="displayTissueShortName();",Class="button")
-		verboseButton = HT.Input(type='button' ,name='dispVerbose',value=' Long Labels ', onClick="displayTissueVerboseName();", Class="button")
-		exportbutton = HT.Input(type='button',  name='export', value='Export', onClick="exportTissueText(allCorrelations);",Class="button")
-		lableNote = HT.Blockquote(HT.Italic(HT.Font('*', color='red',Class="fs9 fwn"), ' Symbol(s) can not be found in database.'))		
-		
-		# flag =1 will show note for "*", which means there's unidentified symbol.
-		if flag==1:
-			form.append(HT.Blockquote(tcmTable,lableNote,HT.P(),shortButton,verboseButton,exportbutton))
-		else:
-			form.append(HT.Blockquote(tcmTable,HT.P(),shortButton,verboseButton,exportbutton))
-			
-		exportScript = """
-			<SCRIPT language=JavaScript>
-			var allCorrelations = %s;
-			</SCRIPT>
-		"""
-		exportScript = exportScript % str(exportArray)
-		self.dict['js1'] = exportScript+'<SCRIPT SRC="/javascript/correlationMatrix.js"></SCRIPT><BR>'
-		
-		TD_LR = HT.TD(colspan=2,width="100%",bgcolor="#eeeeee")
-		TD_LR.append(tissueCorrMatrixHeading,note,Intro,form,HT.P())
-		self.dict['body'] = str(TD_LR)
-		self.dict['title'] = 'Tissue Correlation Result'
-		return
-
-	# Added by NL, 2011-01-06, get all shortNames, verboseNames, verboseNames2, verboseNames3, exportArray 
-	# for Short Label, Long Label, Export functions	
-	def getAllLabelsInfo(self, geneSymbolList=None,geneIdDict=None,ChrDict=None,MbDict=None,descDict=None,pTargetDescDict=None):
-	
-		symbolCount= len(geneSymbolList)
-		geneIdLst =[]
-		exportArray = [([0] * (symbolCount+1))[:] for i in range(symbolCount+1)]
-		exportArray[0][0] = 'Tissue Correlation'
-		shortNames = []
-		verboseNames = []
-		verboseNames2 = []
-		verboseNames3 = []	
-		
-		# added by NL, 2010-12-21, build DIV and array for short label, long label and export functions
-		for i, geneSymbolItem in enumerate(geneSymbolList):
-			geneSymbol =geneSymbolItem.lower()
-			_shortName =HT.Italic("%s" %geneSymbolItem)
-			_verboseName =''
-			_verboseName2 = ''
-			_verboseName3 = ''
-			if geneIdDict.has_key(geneSymbol):
-				geneIdLst.append(geneIdDict[geneSymbol])
-			else:
-				geneIdLst.append(0)
-			if ChrDict.has_key(geneSymbol) and MbDict.has_key(geneSymbol):
-				_verboseName = ' on Chr %s @ %s Mb' % (ChrDict[geneSymbol],MbDict[geneSymbol])
-			if descDict.has_key(geneSymbol):
-				_verboseName2 = '%s' % (descDict[geneSymbol])
-			if pTargetDescDict.has_key(geneSymbol):
-				_verboseName3 = '%s' % (pTargetDescDict[geneSymbol])         
-
-			shortName = HT.Div(id="shortName_" + str(i), style="display:none")
-			shortName.append('Symbol: ')
-			shortName.append(_shortName)
-			shortNames.append(shortName)
-			
-			verboseName = HT.Div(id="verboseName_" + str(i), style="display:none")
-			verboseName.append(_shortName)
-			verboseName.append(_verboseName)
-			verboseNames.append(verboseName)
-			verboseName2 = HT.Div(id="verboseName2_" + str(i), style="display:none")
-			verboseName2.append(_verboseName2)
-			verboseNames2.append(verboseName2)
-			verboseName3 = HT.Div(id="verboseName3_" + str(i), style="display:none")
-			verboseName3.append(_verboseName3)
-			verboseNames3.append(verboseName3)
-			
-			# exportTissueText in webqtl.js is using '/' as delimilator; add '/', otherwise the last letter in geneSymbol will missing
-			exportArray[i+1][0] =geneSymbolItem+ '/' + geneSymbolItem + '/' +geneSymbolItem + ':' + str(_verboseName) + ' : ' + str(_verboseName2) + ' : ' + str(_verboseName3)
-			exportArray[0][i+1] =geneSymbolItem+ '/'	
-
-		return geneIdLst,shortNames, verboseNames, verboseNames2, verboseNames3, exportArray
-
-
-########################################################################
-# functions for display and download when input symbol has only one    #
-########################################################################
-
-	# build header and footer parts for export excel file
-	def createExcelFileWithTitleAndFooter(self, workbook=None, datasetName=None,returnNumber=None):
-
-		worksheet = workbook.add_worksheet()
-		titleStyle = workbook.add_format(align = 'left', bold = 0, size=14, border = 1, border_color="gray")
-
-		##Write title Info
-		worksheet.write([1, 0], "Citations: Please see %s/reference.html" % webqtlConfig.PORTADDR, titleStyle)
-		worksheet.write([2, 0], "Dataset : %s" % datasetName, titleStyle)
-		worksheet.write([3, 0], "Date : %s" % time.strftime("%B %d, %Y", time.gmtime()), titleStyle)
-		worksheet.write([4, 0], "Time : %s GMT" % time.strftime("%H:%M ", time.gmtime()), titleStyle)
-		worksheet.write([5, 0], "Status of data ownership: Possibly unpublished data; please see %s/statusandContact.html for details on sources, ownership, and usage of these data." % webqtlConfig.PORTADDR, titleStyle)
-		#Write footer info
-		worksheet.write([8 + returnNumber, 0], "Funding for The GeneNetwork: NIAAA (U01AA13499, U24AA13513), NIDA, NIMH, and NIAAA (P20-DA21131), NCI MMHCC (U01CA105417), and NCRR (U01NR 105417)", titleStyle)
-		worksheet.write([9 + returnNumber, 0], "PLEASE RETAIN DATA SOURCE INFORMATION WHENEVER POSSIBLE", titleStyle)
-
-		return worksheet
-
-	# build header of table when input symbol has only one
-	def getTableHeader(self, method='0', worksheet=None, newrow=None, headingStyle=None):
-
-		tblobj_header = []
-		exportList=[]
-		header=[]
-		header = [THCell(HT.TD(' ', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), sort=0),
-								  THCell(HT.TD('Symbol',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="symbol", idx=1),
-								  THCell(HT.TD('Description',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="desc", idx=2),
-								  THCell(HT.TD('Location',HT.BR(),'Chr and Mb ', Class="fs13 fwb ffl b1 cw cbrb"), text="location", idx=3),
-								  THCell(HT.TD('N Cases',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text="nstr", idx=4)]
-		if method =="0":# Pearson Correlation		
-			header.append(	THCell(HT.TD(HT.Href(
-										text = HT.Span(' r ', HT.Sup('  ?', style="color:#f00"),HT.BR(),HT.BR(), Class="fs13 fwb ffl cw"),
-										target = '_blank',
-										url = "/correlationAnnotation.html#tissue_r"),
-										Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="tissuecorr", idx=5))
-			header.append(	THCell(HT.TD(HT.Href(
-										text = HT.Span(' p(r) ', HT.Sup('  ?', style="color:#f00"),HT.BR(),HT.BR(), Class="fs13 fwb ffl cw"),
-										target = '_blank',
-										url = "/correlationAnnotation.html#tissue_p_r"),
-										Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="tissuepvalue", idx=6))
-							
-			exportList =[ 'Gene ID',  'Symbol', 'Description', 'Location', 'N Cases', ' r ', ' p(r) ']
-			
-		else:# Spearman Correlation
-			header.append(	THCell(HT.TD(HT.Href(
-										text = HT.Span(' rho ', HT.Sup('  ?', style="color:#f00"),HT.BR(),HT.BR(), Class="fs13 fwb ffl cw"),
-										target = '_blank',
-										url = "/correlationAnnotation.html#tissue_rho"),
-											   Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="tissuecorr", idx=5))
-			header.append(	THCell(HT.TD(HT.Href(
-										text = HT.Span('p(rho)', HT.Sup('  ?', style="color:#f00"),HT.BR(), HT.BR(),Class="fs13 fwb ffl cw"),
-										target = '_blank',
-										url = "/correlationAnnotation.html#tissue_p_rho"),
-										Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="tissuepvalue", idx=6))
-			exportList = ['Gene ID', 'Symbol', 'Description', 'Location', 'N Cases','rho', ' p(rho) ']											
-		
-		# build header of excel for download function
-		for ncol, item in enumerate(exportList):
-			worksheet.write([newrow, ncol], item, headingStyle)
-			worksheet.set_column([ncol, ncol], 2*len(item))
-
-		tblobj_header.append(header)
-
-		return tblobj_header, worksheet
-
-	# build body of table when input symbol has only one
-	def getTableBody(self, symbolCorrDict={}, symbolPvalueDict={},symbolList=[],geneIdDict={},ChrDict={},MbDict={},descDict={},pTargetDescDict={},primarySymbol=None, TissueCount=None,formName=None, worksheet=None, newrow=None,method="0"):
-		
-		tblobj_body = []
-		
-		for symbolItem in symbolList:
-			symbol =symbolItem.lower()
-			if symbol:
-				pass
-			else:
-				symbol ="N/A"
-				
-			if geneIdDict.has_key(symbol) and geneIdDict[symbol]:
-				geneId = geneIdDict[symbol]
-				ncbiUrl = HT.Href(text="NCBI",target='_blank',url=webqtlConfig.NCBI_LOCUSID % geneIdDict[symbol], Class="fs10 fwn")				
-			else:
-				geneId ="N/A"
-				symbolItem =symbolItem.replace('"','') # some symbol is saved in ["symbol"]format
-				ncbiUrl = HT.Href(text="NCBI",target='_blank',url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?CMD=search&DB=gene&term=%s" % symbol, Class="fs10 fwn")
-			
-			_Species="mouse"
-			similarTraitUrl = "%s?cmd=sch&gene=%s&alias=1&species=%s" % (os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), symbolItem, _Species)	
-			gnUrl = HT.Href(text="GN",target='_blank',url=similarTraitUrl, Class="fs10 fwn")
-			
-			tr = []
-			# updated by NL, 04/25/2011: add checkbox and highlight function
-			# first column of table
-			# updated by NL. 12-7-2011
-			tr.append(TDCell(HT.TD(HT.Input(type="checkbox", Class="checkbox", name="tissueResult",value=symbol, onClick="highlight(this)"), align='right',Class="fs12 fwn b1 c222 fsI",nowrap='ON'),symbol,symbol))
-			# updated by NL, 04/26/2011: add GN and NCBI links
-			#gene symbol (symbol column)
-			tr.append(TDCell(HT.TD(HT.Italic(symbolItem), HT.BR(),gnUrl,"&nbsp;&nbsp|&nbsp;&nbsp", ncbiUrl, Class="fs12 fwn b1 c222"),symbolItem, symbolItem))
-
-			#description and probe target description(description column)
-			description_string=''
-			if descDict.has_key(symbol):
-				description_string = str(descDict[symbol]).strip()
-			if pTargetDescDict.has_key(symbol):
-				target_string = str(pTargetDescDict[symbol]).strip()
-
-			description_display = ''
-			if len(description_string) > 1 and description_string != 'None':
-				description_display = description_string
-			else:
-				description_display = symbolItem
-
-			if len(description_display) > 1 and description_display != 'N/A' and len(target_string) > 1 and target_string != 'None':
-				description_display = description_display + '; ' + target_string.strip()
-		
-			tr.append(TDCell(HT.TD(description_display, Class="fs12 fwn b1 c222"), description_display, description_display))
-
-			#trait_location_value is used for sorting (location column)
-			trait_location_repr = 'N/A'
-			trait_location_value = 1000000
-
-			if ChrDict.has_key(symbol) and MbDict.has_key(symbol):
-				
-				if ChrDict[symbol] and MbDict[symbol]:		
-					mb = float(MbDict[symbol])
-					try:
-						trait_location_value = int(ChrDict[symbol])*1000 + mb
-					except:
-						if ChrDict[symbol].upper() == 'X':
-							trait_location_value = 20*1000 + mb
-						else:
-							trait_location_value = ord(str(ChrDict[symbol]).upper()[0])*1000 + mb
-
-					trait_location_repr = 'Chr%s: %.6f' % (ChrDict[symbol], mb )
-				else:
-					trait_location_repr="N/A"
-					trait_location_value ="N/A"
-					
-			tr.append(TDCell(HT.TD(trait_location_repr, Class="fs12 fwn b1 c222", nowrap="on"), trait_location_repr, trait_location_value))
-			
-            # number of overlaped cases  (N Case column)
-			tr.append(TDCell(HT.TD(TissueCount, Class="fs12 fwn ffl b1 c222", align='right'),TissueCount,TissueCount))
-			
-			#tissue correlation (Tissue r column)
-			TCorr = 0.0
-			TCorrStr = "N/A"
-			if symbolCorrDict.has_key(symbol):				
-				TCorr = symbolCorrDict[symbol]
-				TCorrStr = "%2.3f" % TCorr
-				symbol2 =symbolItem.replace('"','') # some symbol is saved in "symbol" format
-				# add a new parameter rankOrder for js function 'showTissueCorrPlot'
-				rankOrder = int(method)
-				TCorrPlotURL = "javascript:showTissueCorrPlot('%s','%s','%s',%d)" %(formName, primarySymbol, symbol2,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:
-				tr.append(TDCell(HT.TD(TCorrStr, Class="fs12 fwn b1 c222", align='right'), TCorrStr, abs(TCorr)))
-
-			#p value of tissue correlation (Tissue p(r) column)
-			TPValue = 1.0
-			TPValueStr = "N/A"
-			if symbolPvalueDict.has_key(symbol):
-				TPValue = symbolPvalueDict[symbol]
-				#TPValueStr = "%2.3f" % TPValue
-				TPValueStr=webqtlUtil.SciFloat(TPValue)
-			tr.append(TDCell(HT.TD(TPValueStr, Class="fs12 fwn b1 c222", align='right'), TPValueStr, TPValue))
-
-			tblobj_body.append(tr)
-			# build body(records) of excel for download function			
-			for ncol, item in enumerate([geneId, symbolItem, description_display, trait_location_repr,TissueCount, TCorr, TPValue]):
-				worksheet.write([newrow, ncol], item)
-
-			newrow += 1
-
-		return tblobj_body, worksheet
-
-		
-	# get return number of records when input symbol has only one
-	def getReturnNum(self,recordReturnNum="0"):
-		if recordReturnNum=="0":
-			returnNum=100
-		elif recordReturnNum=="1":
-			returnNum=200
-		elif recordReturnNum=="2":
-			returnNum=500
-		elif recordReturnNum=="3":
-			returnNum=1000
-		elif recordReturnNum=="4":
-			returnNum=2000
-		elif recordReturnNum=="5":
-			returnNum= None
-			
-		return returnNum
-		
-	# map list based on the order of target List
-	# if item.lower() exist in both lists, then compare the difference of item's original value of two lists
-	# if not equal, then replace the item in targetList by using the item  in primaryList(list from database) 
-	
-	def mappedByTargetList(self,primaryList=[],targetList=[]):
-
-		tempPrimaryList =[x.lower() for x in primaryList]
-		testTargetList =[y.lower() for y in targetList]
-	
-		for i, item in enumerate(tempPrimaryList):
-			if item in testTargetList:
-				index = testTargetList.index(item)
-				if primaryList[i]!=targetList[index]:
-					targetList[index]= primaryList[i]
-
-		return	targetList		
diff --git a/web/webqtl/correlationMatrix/__init__.py b/web/webqtl/correlationMatrix/__init__.py
deleted file mode 100755
index e69de29b..00000000
--- a/web/webqtl/correlationMatrix/__init__.py
+++ /dev/null
diff --git a/web/webqtl/correlationMatrix/tissueCorrelationMatrix.py b/web/webqtl/correlationMatrix/tissueCorrelationMatrix.py
deleted file mode 100755
index 23dc14eb..00000000
--- a/web/webqtl/correlationMatrix/tissueCorrelationMatrix.py
+++ /dev/null
@@ -1,132 +0,0 @@
-# Copyright (C) University of Tennessee Health Science Center, Memphis, TN.
-#
-# This program is free software: you can redistribute it and/or modify it
-# under the terms of the GNU Affero General Public License
-# as published by the Free Software Foundation, either version 3 of the
-# License, or (at your option) any later version.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
-# See the GNU Affero General Public License for more details.
-#
-# This program is available from Source Forge: at GeneNetwork Project
-# (sourceforge.net/projects/genenetwork/).
-#
-# Contact Drs. Robert W. Williams and Xiaodong Zhou (2010)
-# at rwilliams@uthsc.edu and xzhou15@uthsc.edu
-#
-# This module is used by GeneNetwork project (www.genenetwork.org)
-#
-# Created by GeneNetwork Core Team 2010/11/10
-#
-# Last updated by Ning Liu, 2011/01/26
-
-
-#tissueCorrelationMatrix: funciton part for TissueCorrelationPage.py
-from htmlgen import HTMLgen2 as HT
-from correlation import correlationFunction
-from dbFunction import webqtlDatabaseFunction
-import sys
-
-#########################################
-#      Tissue Correlation Page
-#########################################
-
-class  tissueCorrelationMatrix:
-	def __init__(self,tissueProbeSetFreezeId=None):
-		
-		#initialize parameters
-		self.tProbeSetFreezeId = tissueProbeSetFreezeId
-		self.cursor = webqtlDatabaseFunction.getCursor()
-
-
-
-	#retreive dataSet info from database table TissueProbeSetFreeze to get all TissueProbeSetFreezeId(List), Name(List) and FullName(List)
-	def getTissueDataSet(self):	
-		tissProbeSetFreezeIds,Names,fullNames = webqtlDatabaseFunction.getTissueDataSet(cursor=self.cursor)
-		return tissProbeSetFreezeIds,Names,fullNames
-
-
-	#retrieve DatasetName, DatasetFullName based on TissueProbeSetFreezeId, return DatasetName(string), DatasetFullName(string)
-	def getFullnameofCurrentDataset(self):
-	
-		DatasetName, DatasetFullName =webqtlDatabaseFunction.getDatasetNamesByTissueProbeSetFreezeId(cursor=self.cursor, TissueProbeSetFreezeId=self.tProbeSetFreezeId)		
-		return DatasetName, DatasetFullName
-
-				
-	#retrieve how many tissue used in the specific dataset based on TissueProbeSetFreezeId, return TissueCount(int)
-	def getTissueCountofCurrentDataset(self):
-	
-		TissueCount =webqtlDatabaseFunction.getTissueCountByTissueProbeSetFreezeId(cursor=self.cursor,TissueProbeSetFreezeId=self.tProbeSetFreezeId)
-		return TissueCount
-
-
-		
-	#retrieve corrArray(array), pvArray(array) for display by calling  calculation function:calZeroOrderCorrForTiss
-	def getTissueCorrPvArray(self,geneNameLst=None,dataIdDict=None):	
-		#retrieve SymbolValuePairDict(Dict), dictionary of Symbol and Value Pair.key is symbol, value is one list of expression values of one probeSet
-		symbolValuepairDict =correlationFunction.getGeneSymbolTissueValueDict(cursor=self.cursor,symbolList=geneNameLst,dataIdDict=dataIdDict)
-		corrArray,pvArray = correlationFunction.getCorrPvArray(cursor=self.cursor,priGeneSymbolList=geneNameLst,symbolValuepairDict=symbolValuepairDict)
-		return corrArray,pvArray
-
-
-		
-	#retrieve symbolList,geneIdList,dataIdList,ChrList,MbList,descList,pTargetDescList (all are list type) to 
-	#get multi lists for short and long label functions, and for getSymbolValuePairDict and 
-	#getGeneSymbolTissueValueDict to build dict to get CorrPvArray
-	def getTissueProbeSetXRefInfo(self,GeneNameLst=[]):
-		symbolList,geneIdDict,dataIdDict,ChrDict,MbDict,descDict,pTargetDescDict =correlationFunction.getTissueProbeSetXRefInfo(cursor=self.cursor,GeneNameLst=GeneNameLst,TissueProbeSetFreezeId=self.tProbeSetFreezeId)
-		return symbolList,geneIdDict,dataIdDict,ChrDict,MbDict,descDict,pTargetDescDict		
-
-
-
-	#retrieve corrArray(array), pvArray(array) for gene symbol pair
-	def getCorrPvArrayForGeneSymbolPair(self,geneNameLst=None):
-		corrArray = None
-		pvArray = None
-
-		if len(geneNameLst) == 2:
-			#retrieve SymbolValuePairDict(Dict), dictionary of Symbol and Value Pair.key is symbol, value is one list of expression values of one probeSet
-			symbolList,geneIdDict,dataIdDict,ChrDict,MbDict,descDict,pTargetDescDict =correlationFunction.getTissueProbeSetXRefInfo(cursor=self.cursor,GeneNameLst=geneNameLst,TissueProbeSetFreezeId=self.tProbeSetFreezeId)	
-			symbolValuepairDict =correlationFunction.getGeneSymbolTissueValueDict(cursor=self.cursor,symbolList=geneNameLst,dataIdDict=dataIdDict)
-			corrArray,pvArray = correlationFunction.getCorrPvArray(cursor=self.cursor,priGeneSymbolList=geneNameLst,symbolValuepairDict=symbolValuepairDict)
-
-		return corrArray,pvArray
-
-
-	#retrieve symbolCorrDict(dict), symbolPvalueDict(dict) to get all tissues' correlation value and P value; key is symbol	
-	def calculateCorrOfAllTissueTrait(self, primaryTraitSymbol=None, method='0'):
-		symbolCorrDict, symbolPvalueDict = correlationFunction.calculateCorrOfAllTissueTrait(cursor=self.cursor, primaryTraitSymbol=primaryTraitSymbol, TissueProbeSetFreezeId=self.tProbeSetFreezeId,method=method)
-		
-		return symbolCorrDict, symbolPvalueDict
-
-	#Translate GeneId to gene symbol and keep the original order.
-	def getGeneSymbolLst(self, geneSymbols=None):
-		geneSymbolLst=[]
-		geneIdLst=[]
-		#split the input string at every occurrence of the delimiter '\r', and return the substrings in an array. 
-		tokens=geneSymbols.strip().split('\r')
-
-		#Ning: To keep the original order of input symbols and GeneIds
-		for i in tokens:
-			i=i.strip()
-			if (len(i) >0) and (i not in geneSymbolLst):
-				geneSymbolLst.append(i)
-				# if input includes geneId(s), then put it/them into geneIdLst
-				if i.isdigit():
-					geneIdLst.append(i)
-
-		#Ning: Replace GeneId with symbol if applicable
-		if len(geneIdLst)>0:
-			# if input includes geneId(s), replace geneId by geneSymbol; 
-			geneIdSymbolPair =webqtlDatabaseFunction.getGeneIdSymbolPairByGeneId(cursor=self.cursor, geneIdLst =geneIdLst)
-			for geneId in geneIdLst:
-				if geneIdSymbolPair[geneId]:
-					index = geneSymbolLst.index(geneId)
-					geneSymbolLst[index] =geneIdSymbolPair[geneId]
-
-		return geneSymbolLst
-			
-		
-