# 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 GeneNetwork Core Team 2010/10/20 import os import string import piddle as pid import cPickle from htmlgen import HTMLgen2 as HT from base.templatePage import templatePage from base import webqtlConfig from base.webqtlTrait import webqtlTrait from utility import webqtlUtil from utility import Plot import slink # XZ, 09/09/2008: After adding several traits to collection, click "QTL Heatmap" button, # XZ, 09/09/2008: This class will generate what you see. ######################################### # QTL heatmap Page ######################################### class heatmapPage(templatePage): labelFont=pid.Font(ttf="tahoma",size=14,bold=0) topHeight = 0 def __init__(self,fd): templatePage.__init__(self, fd) if not self.openMysql(): return if not fd.genotype: fd.readGenotype() self.searchResult = fd.formdata.getvalue('searchResult') if not self.searchResult: templatePage.__init__(self, fd) heading = 'QTL Heatmap' 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 = string.split(self.searchResult,'\t') if self.searchResult: if len(self.searchResult) > webqtlConfig.MAXCORR: heading = 'QTL Heatmap' detail = ['In order to display the QTL heat map properly, do not select more than %d traits for analysis.' % webqtlConfig.MAXCORR] self.error(heading=heading,detail=detail) return 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 = 'QTL Heatmap' detail = [HT.Font('Error : ',color='red'),HT.Font('Error occurs while retrieving data from database.',color='black')] self.error(heading=heading,detail=detail) return self.colorScheme = fd.formdata.getvalue('colorScheme') if not self.colorScheme: self.colorScheme = '1' self.dict['title'] = 'QTL heatmap' NNN = len(traitList) if NNN == 0: heading = "QTL Heatmap" detail = ['No trait was selected for %s data set. No QTL heatmap was generated.' % fd.RISet] self.error(heading=heading,detail=detail) return elif NNN < 2: templatePage.__init__(self, fd) heading = 'QTL Heatmap' detail = ['You need to select at least two traits in order to generate QTL heatmap.'] self.error(heading=heading,detail=detail) return else: #XZ: It's necessory to define canvas here canvas = pid.PILCanvas(size=(80+NNN*20,880)) names = map(webqtlTrait.displayName, traitList) self.targetDescriptionChecked = fd.formdata.getvalue('targetDescriptionCheck', '') #XZ, 7/29/2009: create trait display and find max strWidth strWidth = 0 for j in range(len(names)): thisTrait = traitList[j] if self.targetDescriptionChecked: if thisTrait.db.type == 'ProbeSet': if thisTrait.probe_target_description: names[j] += ' [%s at Chr %s @ %2.3fMB, %s]' % (thisTrait.symbol, thisTrait.chr, thisTrait.mb, thisTrait.probe_target_description) else: names[j] += ' [%s at Chr %s @ %2.3fMB]' % (thisTrait.symbol, thisTrait.chr, thisTrait.mb) elif thisTrait.db.type == 'Geno': names[j] += ' [Chr %s @ %2.3fMB]' % (thisTrait.chr, thisTrait.mb) elif thisTrait.db.type == 'Publish': if thisTrait.abbreviation: names[j] += ' [%s]' % (thisTrait.abbreviation) else: pass else: pass i = canvas.stringWidth(names[j],font=self.labelFont) if i > strWidth: strWidth = i width = NNN*20 xoffset = 40 yoffset = 40 cellHeight = 3 nLoci = reduce(lambda x,y: x+y, map(lambda x: len(x),fd.genotype),0) if nLoci > 2000: cellHeight = 1 elif nLoci > 1000: cellHeight = 2 elif nLoci < 200: cellHeight = 10 else: pass pos = range(NNN) neworder = [] BWs = Plot.BWSpectrum() colors100 = Plot.colorSpectrum() colors = Plot.colorSpectrum(130) finecolors = Plot.colorSpectrum(250) colors100.reverse() colors.reverse() finecolors.reverse() scaleFont=pid.Font(ttf="tahoma",size=10,bold=0) self.clusterChecked = fd.formdata.getvalue('clusterCheck', '') if not self.clusterChecked: #XZ: this part is for original order for i in range(len(names)): neworder.append((xoffset+20*(i+1), i)) canvas = pid.PILCanvas(size=(80+NNN*20+240,80+ self.topHeight +5+5+strWidth+nLoci*cellHeight+80+20*cellHeight)) self.drawTraitNameBottom(canvas,names,yoffset,neworder,strWidth) else: #XZ: this part is to cluster traits self.topHeight = 400 canvas = pid.PILCanvas(size=(80+NNN*20+240,80+ self.topHeight +5+5+strWidth+nLoci*cellHeight+80+20*cellHeight)) corArray = [([0] * (NNN))[:] for i in range(NNN)] nnCorr = len(fd.strainlist) #XZ, 08/04/2009: I commented out pearsonArray, spearmanArray for i, thisTrait in enumerate(traitList): 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) if (1-corr) < 0: distance = 0.0 else: distance = 1-corr corArray[i][j] = distance corArray[j][i] = distance elif j == i: corArray[i][j] = 0.0 else: pass #XZ, 7/29/2009: The parameter d has info of cluster (group member and distance). The format of d is tricky. Print it out to see it's format. d = slink.slink(corArray) #XZ, 7/29/2009: Attention: The 'neworder' is changed by the 'draw' function #XZ, 7/30/2009: Only toppos[1][0] and top[1][1] are used later. Then what toppos[0] is used for? toppos = self.draw(canvas,names,d,xoffset,yoffset,neworder) self.drawTraitNameTop(canvas,names,yoffset,neworder,strWidth) #XZ, 7/29/2009: draw the top vertical line canvas.drawLine(toppos[1][0],toppos[1][1],toppos[1][0],yoffset) #XZ: draw string 'distance = 1-r' canvas.drawString('distance = 1-r',neworder[-1][0] + 50, self.topHeight*3/4,font=self.labelFont,angle=90) #draw Scale scaleFont=pid.Font(ttf="tahoma",size=10,bold=0) x = neworder[-1][0] canvas.drawLine(x+5, self.topHeight+yoffset, x+5, yoffset, color=pid.black) y = 0 while y <=2: canvas.drawLine(x+5, self.topHeight*y/2.0+yoffset, x+10, self.topHeight*y/2.0+yoffset) canvas.drawString('%2.1f' % (2-y), x+12, self.topHeight*y/2.0+yoffset, font=scaleFont) y += 0.5 chrname = 0 chrnameFont=pid.Font(ttf="tahoma",size=24,bold=0) Ncol = 0 gifmap = HT.Map(name='traitMap') nearestMarkers = self.getNearestMarker(traitList, fd.genotype) # import cPickle sessionfile = fd.formdata.getvalue("session") if sessionfile: fp = open(os.path.join(webqtlConfig.TMPDIR, sessionfile + '.session'), 'rb') permData = cPickle.load(fp) fp.close() else: permData = {} #XZ, 7/31/2009: This for loop is to generate the heatmap #XZ: draw trait by trait instead of marker by marker for order in neworder: #startHeight = 40+400+5+5+strWidth startHeight = self.topHeight + 40+5+5+strWidth startWidth = order[0]-5 if Ncol and Ncol % 5 == 0: drawStartPixel = 8 else: drawStartPixel = 9 tempVal = traitDataList[order[1]] _vals = [] _strains = [] for i in range(len(fd.strainlist)): if tempVal[i] != None: _strains.append(fd.strainlist[i]) _vals.append(tempVal[i]) qtlresult = fd.genotype.regression(strains = _strains, trait = _vals) if sessionfile: LRSArray = permData[str(traitList[order[1]])] else: LRSArray = fd.genotype.permutation(strains = _strains, trait = _vals, nperm = 1000) permData[str(traitList[order[1]])] = LRSArray sugLRS = LRSArray[369] sigLRS = LRSArray[949] prechr = 0 chrstart = 0 nearest = nearestMarkers[order[1]] midpoint = [] for item in qtlresult: if item.lrs > webqtlConfig.MAXLRS: adjustlrs = webqtlConfig.MAXLRS else: adjustlrs = item.lrs if item.locus.chr != prechr: if prechr: canvas.drawRect(startWidth-drawStartPixel, startHeight, startWidth+10, startHeight+3,edgeColor=pid.white, edgeWidth=0, fillColor=pid.white) startHeight+= 3 if not chrname: canvas.drawString(prechr,xoffset-20,(chrstart+startHeight)/2,font = chrnameFont,color=pid.dimgray) prechr = item.locus.chr chrstart = startHeight if self.colorScheme == '0': if adjustlrs <= sugLRS: colorIndex = int(65*adjustlrs/sugLRS) else: colorIndex = int(65 + 35*(adjustlrs-sugLRS)/(sigLRS-sugLRS)) if colorIndex > 99: colorIndex = 99 colorIndex = colors100[colorIndex] elif self.colorScheme == '1': sugLRS = LRSArray[369]/2.0 if adjustlrs <= sugLRS: colorIndex = BWs[20+int(50*adjustlrs/sugLRS)] else: if item.additive > 0: colorIndex = int(80 + 50*(adjustlrs-sugLRS)/(sigLRS-sugLRS)) else: colorIndex = int(50 - 50*(adjustlrs-sugLRS)/(sigLRS-sugLRS)) if colorIndex > 129: colorIndex = 129 if colorIndex < 0: colorIndex = 0 colorIndex = colors[colorIndex] elif self.colorScheme == '2': if item.additive > 0: colorIndex = int(150 + 100*(adjustlrs/sigLRS)) else: colorIndex = int(100 - 100*(adjustlrs/sigLRS)) if colorIndex > 249: colorIndex = 249 if colorIndex < 0: colorIndex = 0 colorIndex = finecolors[colorIndex] else: colorIndex = pid.white if startHeight > 1: canvas.drawRect(startWidth-drawStartPixel, startHeight, startWidth+10, startHeight+cellHeight,edgeColor=colorIndex, edgeWidth=0, fillColor=colorIndex) else: canvas.drawLine(startWidth-drawStartPixel, startHeight, startWidth+10, startHeight, Color=colorIndex) if item.locus.name == nearest: midpoint = [startWidth,startHeight-5] startHeight+=cellHeight #XZ, map link to trait name and band COORDS = "%d,%d,%d,%d" %(startWidth-drawStartPixel,self.topHeight+40,startWidth+10,startHeight) HREF = "javascript:showDatabase2('%s','%s','%s');" % (traitList[order[1]].db.name, traitList[order[1]].name, traitList[order[1]].cellid) Areas = HT.Area(shape='rect',coords=COORDS,href=HREF, title='%s' % names[order[1]]) gifmap.areas.append(Areas) if midpoint: traitPixel = ((midpoint[0],midpoint[1]),(midpoint[0]-6,midpoint[1]+12),(midpoint[0]+6,midpoint[1]+12)) canvas.drawPolygon(traitPixel,edgeColor=pid.black,fillColor=pid.orange,closed=1) if not chrname: canvas.drawString(prechr,xoffset-20,(chrstart+startHeight)/2,font = chrnameFont,color=pid.dimgray) chrname = 1 Ncol += 1 #draw Spectrum startSpect = neworder[-1][0] + 30 startHeight = self.topHeight + 40+5+5+strWidth if self.colorScheme == '0': for i in range(100): canvas.drawLine(startSpect+i,startHeight+20,startSpect+i,startHeight+40,color=colors100[i]) scaleFont=pid.Font(ttf="tahoma",size=10,bold=0) canvas.drawLine(startSpect,startHeight+45,startSpect,startHeight+39,color=pid.black) canvas.drawString('LRS = 0',startSpect,startHeight+55,font=scaleFont) canvas.drawLine(startSpect+64,startHeight+45,startSpect+64,startHeight+39,color=pid.black) canvas.drawString('Suggestive LRS',startSpect+64,startHeight+55,font=scaleFont) canvas.drawLine(startSpect+99,startHeight+45,startSpect+99,startHeight+39,color=pid.black) canvas.drawString('Significant LRS',startSpect+105,startHeight+40,font=scaleFont) elif self.colorScheme == '1': for i in range(50): canvas.drawLine(startSpect+i,startHeight,startSpect+i,startHeight+40,color=BWs[20+i]) for i in range(50,100): canvas.drawLine(startSpect+i,startHeight,startSpect+i,startHeight+20,color=colors[100-i]) canvas.drawLine(startSpect+i,startHeight+20,startSpect+i,startHeight+40,color=colors[30+i]) canvas.drawLine(startSpect,startHeight+45,startSpect,startHeight+39,color=pid.black) canvas.drawString('LRS = 0',startSpect,startHeight+60,font=scaleFont) canvas.drawLine(startSpect+50,startHeight+45,startSpect+50,startHeight+39,color=pid.black) canvas.drawString('0.5*Suggestive LRS',startSpect+50,startHeight+ 60,font=scaleFont) canvas.drawLine(startSpect+99,startHeight+45,startSpect+99,startHeight+39,color=pid.black) canvas.drawString('Significant LRS',startSpect+105,startHeight+50,font=scaleFont) textFont=pid.Font(ttf="verdana",size=18,bold=0) canvas.drawString('%s +' % fd.ppolar,startSpect+120,startHeight+ 35,font=textFont,color=pid.red) canvas.drawString('%s +' % fd.mpolar,startSpect+120,startHeight+ 15,font=textFont,color=pid.blue) elif self.colorScheme == '2': for i in range(100): canvas.drawLine(startSpect+i,startHeight,startSpect+i,startHeight+20,color=finecolors[100-i]) canvas.drawLine(startSpect+i,startHeight+20,startSpect+i,startHeight+40,color=finecolors[150+i]) canvas.drawLine(startSpect,startHeight+45,startSpect,startHeight+39,color=pid.black) canvas.drawString('LRS = 0',startSpect,startHeight+60,font=scaleFont) canvas.drawLine(startSpect+99,startHeight+45,startSpect+99,startHeight+39,color=pid.black) canvas.drawString('Significant LRS',startSpect+105,startHeight+50,font=scaleFont) textFont=pid.Font(ttf="verdana",size=18,bold=0) canvas.drawString('%s +' % fd.ppolar,startSpect+120,startHeight+ 35,font=textFont,color=pid.red) canvas.drawString('%s +' % fd.mpolar,startSpect+120,startHeight+ 15,font=textFont,color=pid.blue) filename= webqtlUtil.genRandStr("Heatmap_") canvas.save(webqtlConfig.IMGDIR+filename, format='png') img2=HT.Image('/image/'+filename+'.png',border=0,usemap='#traitMap') imgUrl = 'Right-click or control-click on the link to download this graph as a <a href="/image/%s.png" class="normalsize" target="_blank">PNG file</a>' % filename 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':fd.RISet+"Geno",'CellID':'_','RISet':fd.RISet,'searchResult':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')) heatmap = HT.Input(type='button' ,name='mintmap',value='Redraw QTL Heatmap', onClick="databaseFunc(this.form,'heatmap');",Class="button") spects = {'0':'Single Spectrum','1':'Grey + Blue + Red','2':'Blue + Red'} schemeMenu = HT.Select(name='colorScheme') schemeMenu.append(('Single Spectrum',0)) schemeMenu.append(('Grey + Blue + Red',1)) schemeMenu.append(('Blue + Red',2)) schemeMenu.selected.append(spects[self.colorScheme]) clusterCheck= HT.Input(type='checkbox', Class='checkbox', name='clusterCheck',checked=0) targetDescriptionCheck = HT.Input(type='checkbox', Class='checkbox', name='targetDescriptionCheck',checked=0) form.append(gifmap,schemeMenu, heatmap, HT.P(), clusterCheck, ' Cluster traits ', targetDescriptionCheck, ' Add description', HT.P(),img2, HT.P(), imgUrl) if not sessionfile: filename = webqtlUtil.generate_session() webqtlUtil.dump_session(permData, os.path.join(webqtlConfig.TMPDIR, filename +'.session')) sessionfile=filename form.append(HT.Input(name='session', value=sessionfile, type='hidden')) heatmapHelp = HT.Input(type='button' ,name='heatmapHelpButton',value='Info', onClick="openNewWin('/heatmap.html');",Class="button") heatmapHeading = HT.Paragraph('QTL Heatmap ', heatmapHelp, Class="title") TD_LR = HT.TD(colspan=2,height=200,width="100%",bgColor='#eeeeee') TD_LR.append(heatmapHeading, HT.P(),HT.P(),HT.P(),HT.P(),HT.P(),form) self.dict['body'] = str(TD_LR) #XZ, 7/31/2009: This function put the order of traits into parameter neworder, #XZ: return the position of the top vertical line of the hierarchical tree, draw the hierarchical tree. def draw(self,canvas,names,d,xoffset,yoffset,neworder): maxDistance = self.topHeight fontoffset = 4 #XZ, 7/31/2009: used only for drawing tree if type(d[0]) == type(1) and type(d[1]) == type(1): neworder.append((xoffset+20,d[0])) neworder.append((xoffset+40,d[1])) height = d[2]*maxDistance/2 canvas.drawLine(xoffset+20-fontoffset,maxDistance+yoffset,xoffset+20-fontoffset,maxDistance-height+yoffset) canvas.drawLine(xoffset+40-fontoffset,maxDistance+yoffset,xoffset+40-fontoffset,maxDistance-height+yoffset) canvas.drawLine(xoffset+40-fontoffset,maxDistance+yoffset-height,xoffset+20-fontoffset,maxDistance-height+yoffset) return (40,(xoffset+30-fontoffset,maxDistance-height+yoffset)) elif type(d[0]) == type(1): neworder.append((xoffset+20,d[0])) d2 = self.draw(canvas,names,d[1],xoffset+20,yoffset,neworder) height = d[2]*maxDistance/2 canvas.drawLine(xoffset+20-fontoffset,maxDistance+yoffset,xoffset+20-fontoffset,maxDistance-height+yoffset) canvas.drawLine(d2[1][0],d2[1][1],d2[1][0],maxDistance-height+yoffset) canvas.drawLine(d2[1][0],maxDistance-height+yoffset,xoffset+20-fontoffset,maxDistance-height+yoffset) return (20+d2[0],((d2[1][0]+xoffset+20-fontoffset)/2,maxDistance-height+yoffset)) elif type(d[1]) == type(1): d1 = self.draw(canvas,names,d[0],xoffset,yoffset,neworder) neworder.append((xoffset+d1[0]+20,d[1])) height = d[2]*maxDistance/2 canvas.drawLine(xoffset+d1[0]+20-fontoffset,maxDistance+yoffset,xoffset+d1[0]+20-fontoffset,maxDistance-height+yoffset) canvas.drawLine(d1[1][0],d1[1][1],d1[1][0],maxDistance-height+yoffset) canvas.drawLine(d1[1][0],maxDistance-height+yoffset,xoffset+d1[0]+20-fontoffset,maxDistance-height+yoffset) return (d1[0]+20,((d1[1][0]+xoffset+d1[0]+20-fontoffset)/2,maxDistance-height+yoffset)) else: d1 = self.draw(canvas,names,d[0],xoffset,yoffset,neworder) d2 = self.draw(canvas,names,d[1],xoffset+d1[0],yoffset,neworder) height = d[2]*maxDistance/2 canvas.drawLine(d2[1][0],d2[1][1],d2[1][0],maxDistance-height+yoffset) canvas.drawLine(d1[1][0],d1[1][1],d1[1][0],maxDistance-height+yoffset) canvas.drawLine(d1[1][0],maxDistance-height+yoffset,d2[1][0],maxDistance-height+yoffset) return (d1[0]+d2[0],((d1[1][0]+d2[1][0])/2,maxDistance-height+yoffset)) #XZ, 7/31/2009: dras trait names def drawTraitNameBottom (self,canvas,names,yoffset,neworder,strWidth): maxDistance = self.topHeight for oneOrder in neworder: canvas.drawString(names[oneOrder[1]],oneOrder[0]-5,maxDistance+yoffset+5+strWidth-canvas.stringWidth(names[oneOrder[1]],font=self.labelFont),font=self.labelFont,color=pid.black,angle=270) def drawTraitNameTop (self,canvas,names,yoffset,neworder,strWidth): maxDistance = self.topHeight for oneOrder in neworder: canvas.drawString(names[oneOrder[1]],oneOrder[0]-5,maxDistance+yoffset+5,font=self.labelFont,color=pid.black,angle=270) def getNearestMarker(self,traitList, genotype): out = [] if not genotype.Mbmap: return [None]* len(traitList) for item in traitList: try: nearest = None for _chr in genotype: if _chr.name != item.chr: continue distance = 1e30 for _locus in _chr: if abs(_locus.Mb-item.mb) < distance: distance = abs(_locus.Mb-item.mb) nearest = _locus.name out.append(nearest) except: out.append(None) return out