diff options
Diffstat (limited to 'web/webqtl/correlationMatrix')
| -rwxr-xr-x | web/webqtl/correlationMatrix/CorrelationMatrixPage.py | 595 | ||||
| -rwxr-xr-x | web/webqtl/correlationMatrix/TissueAbbreviationPage.py | 79 | ||||
| -rwxr-xr-x | web/webqtl/correlationMatrix/TissueCorrelationPage.py | 673 | ||||
| -rwxr-xr-x | web/webqtl/correlationMatrix/__init__.py | 0 | ||||
| -rwxr-xr-x | web/webqtl/correlationMatrix/tissueCorrelationMatrix.py | 132 |
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 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 ', Class=abbrHeaderStyle, NOWRAP = 1),HT.TD('Full Name ', 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(" "),dataSetMenu,InfoFile,HT.BR()); - - form.append(HT.BR(),HT.Strong(" Please enter only one gene symbol/ENTREZ gene Id per line."),HT.BR(),HT.Strong(" "),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(" "),HT.Span("Return:", Class="ffl fwb fs12"),HT.Strong(" "),recordReturnMenu,HT.BR()); - form.append(HT.BR(),HT.Strong(" "),'Pearson',calculateMethodMenu," "*3,'Spearman Rank',calculateMethodMenu1,HT.BR(),HT.BR()); - form.append(HT.Strong(" "),HT.Input(type="button", value=" Compute ", Class="button",onClick="selectFormIdForTissueCorr('%s');"%formName)) - form.append(HT.Strong(" "),HT.Input(type="button", Class="button", value=" Make Default ", 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. ["%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 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,"  |  ", 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 - - - |