def __init__(self,fd):
templatePage.__init__(self, fd)
filename = self.session("Genome Association Result", "Computing Genome Association Results")
webqtlUtil.dump_session(fd, os.path.join(webqtlConfig.TMPDIR, filename +'.session'))
url = webqtlConfig.REFRESHDIR % (webqtlConfig.CGIDIR, self.filename)
os.system("%s %swebqtlCmdLine.py markerRegression %s >/dev/null 2>&1 &" % (webqtlConfig.PythonPath, webqtlConfig.CMDLINEDIR, filename))
self.redirection = url
def __init__(self,fd):
templatePage.__init__(self, fd)
filename = self.session("Partial Correlation", "Partial Correlation in Progress")
webqtlUtil.dump_session(fd, os.path.join(webqtlConfig.TMPDIR, filename +'.session'))
url = webqtlConfig.REFRESHDIR % (webqtlConfig.CGIDIR, self.filename)
os.system("%s %swebqtlCmdLine.py partialCorrelation %s >/dev/null 2>&1 &" % (webqtlConfig.PythonPath, webqtlConfig.CMDLINEDIR, filename))
self.redirection = url
def __init__(self,fd):
templatePage.__init__(self, fd)
filename = self.session("QTL Heatmap", "Computing QTL Heatmap")
webqtlUtil.dump_session(fd, os.path.join(webqtlConfig.TMPDIR, filename +'.session'))
url = webqtlConfig.REFRESHDIR % (webqtlConfig.CGIDIR, self.filename)
os.system("%s %swebqtlCmdLine.py heatmap %s >/dev/null 2>&1 &" % (webqtlConfig.PythonPath, webqtlConfig.CMDLINEDIR, filename))
self.redirection = url
def __init__(self,fd):
templatePage.__init__(self, fd)
filename = self.session("Generate Report v2", "Generating Report v2. Please be Patient")
webqtlUtil.dump_session(fd, os.path.join(webqtlConfig.TMPDIR, filename +'.session'))
url = webqtlConfig.REFRESHDIR % (webqtlConfig.CGIDIR, self.filename)
os.system("%s %swebqtlCmdLine.py genreport2 %s >/dev/null 2>&1 &" % (webqtlConfig.PythonPath, webqtlConfig.CMDLINEDIR, filename))
self.redirection = url
def __init__(self,fd):
templatePage.__init__(self, fd)
wtext = "Mapping "
try:
selectedChr = int(fd.formdata.getvalue('chromosomes')) + 1
if selectedChr < 1:
raise "ValueError"
if selectedChr == 21 or (selectedChr == 20 and fd.RISet != 'HXBBXH'):
selectedChr = 'X'
wtext += 'chromosome %s ' % selectedChr
except:
wtext += 'whole genome '
perm = 0
if fd.formdata.getvalue('permCheck'):
perm = 1
wtext += 'with %d permutation tests ' % fd.nperm
boot = 0
if fd.formdata.getvalue('bootCheck'):
boot = 1
if perm:
wtext += 'and %d bootstrap tests ' % fd.nboot
else:
wtext += 'with %d bootstrap tests ' % fd.nboot
if boot == 0 and perm == 0:
wtext += "without permutation or bootstrap tests"
filename = self.session("Interval Mapping", wtext)
webqtlUtil.dump_session(fd, os.path.join(webqtlConfig.TMPDIR, filename +'.session'))
url = webqtlConfig.REFRESHDIR % (webqtlConfig.CGIDIR, self.filename)
os.system("%s %swebqtlCmdLine.py interval %s >/dev/null 2>&1 &" % (webqtlConfig.PythonPath, webqtlConfig.CMDLINEDIR, filename))
self.redirection = url
def buildCanvas(self, colorScheme='', targetDescriptionChecked='', clusterChecked='', sessionfile='', genotype=None, strainlist=None, ppolar=None, mpolar=None, traitList=None, traitDataList=None, userPrivilege=None, userName=None):
labelFont = pid.Font(ttf="tahoma",size=14,bold=0)
topHeight = 0
NNN = len(traitList)
#XZ: It's necessory to define canvas here
canvas = pid.PILCanvas(size=(80+NNN*20,880))
names = map(webqtlTrait.displayName, traitList)
#XZ, 7/29/2009: create trait display and find max strWidth
strWidth = 0
for j in range(len(names)):
thisTrait = traitList[j]
if 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.confidential:
if webqtlUtil.hasAccessToConfidentialPhenotypeTrait(privilege=userPrivilege, userName=userName, authorized_users=thisTrait.authorized_users):
if thisTrait.post_publication_abbreviation:
names[j] += ' [%s]' % (thisTrait.post_publication_abbreviation)
else:
if thisTrait.pre_publication_abbreviation:
names[j] += ' [%s]' % (thisTrait.pre_publication_abbreviation)
else:
if thisTrait.post_publication_abbreviation:
names[j] += ' [%s]' % (thisTrait.post_publication_abbreviation)
else:
pass
i = canvas.stringWidth(names[j], font=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),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)
if not 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+ topHeight +5+5+strWidth+nLoci*cellHeight+80+20*cellHeight))
self.drawTraitNameBottom(canvas,names,yoffset,neworder,strWidth,topHeight,labelFont)
else: #XZ: this part is to cluster traits
topHeight = 400
canvas = pid.PILCanvas(size=(80+NNN*20+240,80+ topHeight +5+5+strWidth+nLoci*cellHeight+80+20*cellHeight))
corArray = [([0] * (NNN))[:] for i in range(NNN)]
nnCorr = len(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,topHeight)
self.drawTraitNameTop(canvas,names,yoffset,neworder,strWidth,topHeight,labelFont)
#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, topHeight*3/4,font=labelFont,angle=90)
#draw Scale
scaleFont=pid.Font(ttf="tahoma",size=10,bold=0)
x = neworder[-1][0]
canvas.drawLine(x+5, topHeight+yoffset, x+5, yoffset, color=pid.black)
y = 0
while y <=2:
canvas.drawLine(x+5, topHeight*y/2.0+yoffset, x+10, topHeight*y/2.0+yoffset)
canvas.drawString('%2.1f' % (2-y), x+12, topHeight*y/2.0+yoffset, font=scaleFont)
y += 0.5
chrname = 0
chrnameFont=pid.Font(ttf="tahoma",size=24,bold=0)
Ncol = 0
nearestMarkers = self.getNearestMarker(traitList, genotype)
# import cPickle
if sessionfile:
fp = open(os.path.join(webqtlConfig.TMPDIR, sessionfile + '.session'), 'rb')
permData = cPickle.load(fp)
fp.close()
else:
permData = {}
areas = []
#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 = 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(strainlist)):
if tempVal[i] != None:
_strains.append(strainlist[i])
_vals.append(tempVal[i])
qtlresult = genotype.regression(strains = _strains, trait = _vals)
if sessionfile:
LRSArray = permData[str(traitList[order[1]])]
else:
LRSArray = 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 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 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 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,topHeight+40,startWidth+10,startHeight)
HREF = "javascript:showDatabase2('%s','%s','%s');" % (traitList[order[1]].db.name, traitList[order[1]].name, traitList[order[1]].cellid)
area = (COORDS, HREF, '%s' % names[order[1]])
areas.append(area)
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 = topHeight + 40+5+5+strWidth
if 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 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 +' % ppolar,startSpect+120,startHeight+ 35,font=textFont,color=pid.red)
canvas.drawString('%s +' % mpolar,startSpect+120,startHeight+ 15,font=textFont,color=pid.blue)
elif 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 +' % ppolar,startSpect+120,startHeight+ 35,font=textFont,color=pid.red)
canvas.drawString('%s +' % mpolar,startSpect+120,startHeight+ 15,font=textFont,color=pid.blue)
filename= webqtlUtil.genRandStr("Heatmap_")
canvas.save(webqtlConfig.IMGDIR+filename, format='png')
if not sessionfile:
sessionfile = webqtlUtil.generate_session()
webqtlUtil.dump_session(permData, os.path.join(webqtlConfig.TMPDIR, sessionfile +'.session'))
self.filename=filename
self.areas=areas
self.sessionfile=sessionfile
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)
def __init__(self,fd,InputData=None):
templatePage.__init__(self, fd)
if not self.openMysql():
return
if not fd.genotype:
fd.readGenotype()
self.searchResult = fd.formdata.getvalue('searchResult')
self.tissueProbeSetFeezeId = "1" #XZ, Jan 03, 2010: currently, this dataset is "UTHSC Illumina V6.2 RankInv B6 D2 average CNS GI average (May 08)"
TissueCorrMatrixObject = tissueCorrelationMatrix(tissueProbeSetFreezeId=self.tissueProbeSetFeezeId)
if type("1") == type(self.searchResult):
self.searchResult = string.split(self.searchResult, '\t')
if (not self.searchResult or (len(self.searchResult) < 2)):
heading = 'Network Graph'
detail = ['You need to select at least two traits in order to generate Network Graph.']
self.error(heading=heading,detail=detail)
print 'Content-type: text/html\n'
self.write()
return
if self.searchResult:
if len(self.searchResult) > webqtlConfig.MAXCORR:
heading = 'Network Graph'
detail = ['In order to display Network Graph properly, Do not select more than %d traits for Network Graph.' % webqtlConfig.MAXCORR]
self.error(heading=heading,detail=detail)
print 'Content-type: text/html\n'
self.write()
return
else:
pass
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 = 'Network Graph'
detail = [HT.Font('Error : ',color='red'),HT.Font('Error occurs while retrieving data from database.',color='black')]
self.error(heading=heading,detail=detail)
print 'Content-type: text/html\n'
self.write()
return
NNN = len(traitList)
if NNN < 2:
templatePage.__init__(self, fd)
heading = 'Network Graph'
detail = ['You need to select at least two traits in order to generate a Network Graph']
print 'Content-type: text/html\n'
self.write()
return
else:
pearsonArray = [([0] * (NNN))[:] for i in range(NNN)]
spearmanArray = [([0] * (NNN))[:] for i in range(NNN)]
GeneIdArray = []
GeneSymbolList = [] #XZ, Jan 03, 2011: holds gene symbols for calculating tissue correlation
traitInfoArray = []
i = 0
nnCorr = len(fd.strainlist)
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)
pearsonArray[i][j] = corr
pearsonArray[j][i] = corr
elif j == i:
pearsonArray[i][j] = 1.0
spearmanArray[i][j] = 1.0
else:
corr,nOverlap = webqtlUtil.calCorrelationRank(traitDataList[i],traitDataList[j],nnCorr)
spearmanArray[i][j] = corr
spearmanArray[j][i] = corr
GeneId1 = None
tmpSymbol = None
if thisTrait.db.type == 'ProbeSet':
try:
GeneId1 = int(thisTrait.geneid)
except:
GeneId1 = 0
if thisTrait.symbol:
tmpSymbol = thisTrait.symbol.lower()
GeneIdArray.append(GeneId1)
GeneSymbolList.append(tmpSymbol)
_traits = []
_matrix = []
for i in range(NNN):
turl = webqtlConfig.CGIDIR + webqtlConfig.SCRIPTFILE + '?FormID=showDatabase&database=%s&ProbeSetID=%s' % (traitList[i].db.name, traitList[i].name)
if traitList[i].cellid:
turl += "&CellID=%s" % traitList[i].cellid
if traitList[i].db.type == 'ProbeSet':
if traitList[i].symbol:
_symbol = traitList[i].symbol
else:
_symbol = 'unknown'
elif traitList[i].db.type == 'Publish':
_symbol = traitList[i].name
if traitList[i].confidential:
if webqtlUtil.hasAccessToConfidentialPhenotypeTrait(privilege=self.privilege, userName=self.userName, authorized_users=traitList[i].authorized_users):
if traitList[i].post_publication_abbreviation:
_symbol = traitList[i].post_publication_abbreviation
else:
if traitList[i].pre_publication_abbreviation:
_symbol = traitList[i].pre_publication_abbreviation
else:
if traitList[i].post_publication_abbreviation:
_symbol = traitList[i].post_publication_abbreviation
#XZ, 05/26/2009: Xiaodong add code for Geno data
elif traitList[i].db.type == 'Geno':
_symbol = traitList[i].name
else:
_symbol = traitList[i].description
#####if this trait entered by user
if _symbol.__contains__('entered'):
_symbol = _symbol[:_symbol.index('entered')]
#####if this trait generaged by genenetwork
elif _symbol.__contains__('generated'):
_symbol = _symbol[_symbol.rindex(':')+1:]
newTrait = smpTrait.Trait(name=str(traitList[i]), href=turl, symbol=_symbol)
newTrait.color = "black"
_traits.append(newTrait)
for j in range(i+1, NNN):
dataPoint = smpTrait.RawPoint(i, j)
dataPoint.spearman = spearmanArray[i][j]
dataPoint.pearson = pearsonArray[i][j]
#XZ: get literature correlation info.
if GeneIdArray[i] and GeneIdArray[j]:
if GeneIdArray[i] == GeneIdArray[j]:
dataPoint.literature = 1
else:
self.cursor.execute("SELECT Value from LCorrRamin3 WHERE (GeneId1 = %d and GeneId2 = %d) or (GeneId1 = %d and GeneId2 = %d)" % (GeneIdArray[i], GeneIdArray[j], GeneIdArray[j], GeneIdArray[i]))
try:
dataPoint.literature = self.cursor.fetchone()[0]
except:
dataPoint.literature = 0
else:
dataPoint.literature = 0
#XZ: get tissue correlation info
if GeneSymbolList[i] and GeneSymbolList[j]:
dataPoint.tissue = 0
geneSymbolPair = []
geneSymbolPair.append(GeneSymbolList[i])
geneSymbolPair.append(GeneSymbolList[j])
corrArray,pvArray = TissueCorrMatrixObject.getCorrPvArrayForGeneSymbolPair(geneNameLst=geneSymbolPair)
if corrArray[1][0]:
dataPoint.tissue = corrArray[1][0]
else:
dataPoint.tissue = 0
_matrix.append(dataPoint)
OrigDir = os.getcwd()
sessionfile = fd.formdata.getvalue('session')
inputFilename = fd.formdata.getvalue('inputFile')
#If there is no sessionfile generate one and dump all matrix/trait values
if not sessionfile:
filename = webqtlUtil.generate_session()
webqtlUtil.dump_session([_matrix, _traits], os.path.join(webqtlConfig.TMPDIR, filename + '.session'))
sessionfile = filename
startTime = time.time()
#Build parameter dictionary used by networkGraphPage class using buildParamDict function
params = networkGraphUtils.buildParamDict(fd, sessionfile)
nodes = len(_traits)
rawEdges = len(_matrix)
if params["tune"] == "yes":
params = networkGraphUtils.tuneParamDict(params, nodes, rawEdges)
matrix = networkGraphUtils.filterDataMatrix(_matrix, params)
optimalNode = networkGraphUtils.optimalRadialNode(matrix)
if not inputFilename:
inputFilename = tempfile.mktemp()
inputFilename = webqtlConfig.IMGDIR + inputFilename.split("/")[2]
#writes out 4 graph files for exporting
graphFile = "/image/" + networkGraphUtils.writeGraphFile(matrix, _traits, inputFilename, params)
networkGraphUtils.processDataMatrix(matrix, params)
edges = 0
for edge in matrix:
if edge.value != 0:
edges +=1
for trait in _traits:
trait.name = networkGraphUtils.fixLabel(trait.name)
RootDir = webqtlConfig.IMGDIR
RootDirURL = "/image/"
#This code writes the datafile that the graphviz function runNeato uses to generate the
#"digraph" file that defines the graphs parameters
datafile = networkGraphUtils.writeNeatoFile(matrix=matrix, traits=_traits, filename=inputFilename, GeneIdArray=GeneIdArray, p=params)
#Generate graph in various file types
layoutfile = networkGraphUtils.runNeato(datafile, "dot", "dot", params["gType"]) # XZ, 09/11/2008: add module name
# ZS 03/04/2010 This second output file (layoutfile_pdf) is rotated by 90 degrees to prevent an issue with pdf output being cut off at the edges
layoutfile_pdf = networkGraphUtils.runNeato(datafile + "_pdf", "dot", "dot", params["gType"]) # ZS 03/04/2010
pngfile = networkGraphUtils.runNeato(layoutfile, "png", "png", params["gType"])
mapfile = networkGraphUtils.runNeato(layoutfile, "cmapx", "cmapx", params["gType"])# XZ, 09/11/2008: add module name
giffile = networkGraphUtils.runNeato(layoutfile, "gif", "gif", params["gType"])# XZ, 09/11/2008:add module name
psfile = networkGraphUtils.runNeato(layoutfile_pdf, "ps", "ps", params["gType"])# XZ, 09/11/2008: add module name
pdffile = networkGraphUtils.runPsToPdf(psfile, params["width"], params["height"])# XZ, 09/11/2008: add module name
#This generates text files in XGGML (standardized graphing language) and plain text
#so the user can create his/her own graphs in a program like Cytoscape
htmlfile1 = datafile + ".html"
htmlfile2 = datafile + ".graph.html"
os.chdir(OrigDir)
#This generates the graph in various image formats
giffile = RootDirURL + giffile
pngfile = RootDirURL + pngfile
pdffile = RootDirURL + pdffile
endTime = time.time()
totalTime = endTime - startTime
os.chdir(RootDir)
page2 = GraphPage(giffile, mapfile)
page2.writeToFile(htmlfile2)
#This generates the HTML for the body of the Network Graph page
page1 = networkGraphPageBody(fd, matrix, _traits, htmlfile2, giffile, pdffile, nodes, edges, rawEdges, totalTime, params, page2.content, graphFile, optimalNode)
#Adds the javascript colorSel to the body to allow line color selection
self.dict["js1"] = '<SCRIPT SRC="/javascript/colorSel.js"></SCRIPT><BR>'
#self.dict["js1"] += '<SCRIPT SRC="/javascript/networkGraph.js"></SCRIPT>'
#Set body of current templatePage to body of the templatePage networkGraphPage
self.dict['body'] = page1.dict['body']
