def plotNormalProbability(vals=None, RISet='', title=None, showstrains=0, specialStrains=[None], size=(750,500)):
dataXZ = vals[:]
dataXZ.sort(webqtlUtil.cmpOrder)
dataLabel = []
dataX = map(lambda X: X[1], dataXZ)
showLabel = showstrains
if len(dataXZ) > 50:
showLabel = 0
for item in dataXZ:
strainName = webqtlUtil.genShortStrainName(RISet=RISet, input_strainName=item[0])
dataLabel.append(strainName)
dataY=Plot.U(len(dataX))
dataZ=map(Plot.inverseCumul,dataY)
c = pid.PILCanvas(size=(750,500))
Plot.plotXY(c, dataZ, dataX, dataLabel = dataLabel, XLabel='Expected Z score', connectdot=0, YLabel='Trait value', title=title, specialCases=specialStrains, showLabel = showLabel)
filename= webqtlUtil.genRandStr("nP_")
c.save(webqtlConfig.IMGDIR+filename, format='gif')
img=HT.Image('/image/'+filename+'.gif',border=0)
return img
def plotBoxPlot(vals):
valsOnly = []
dataXZ = vals[:]
for i in range(len(dataXZ)):
valsOnly.append(dataXZ[i][1])
plotHeight = 320
plotWidth = 220
xLeftOffset = 60
xRightOffset = 40
yTopOffset = 40
yBottomOffset = 60
canvasHeight = plotHeight + yTopOffset + yBottomOffset
canvasWidth = plotWidth + xLeftOffset + xRightOffset
canvas = pid.PILCanvas(size=(canvasWidth,canvasHeight))
XXX = [('', valsOnly[:])]
Plot.plotBoxPlot(canvas, XXX, offset=(xLeftOffset, xRightOffset, yTopOffset, yBottomOffset), XLabel= "Trait")
filename= webqtlUtil.genRandStr("Box_")
canvas.save(webqtlConfig.IMGDIR+filename, format='gif')
img=HT.Image('/image/'+filename+'.gif',border=0)
plotLink = HT.Span("More about ", HT.Href(text="Box Plots", url="http://davidmlane.com/hyperstat/A37797.html", target="_blank", Class="fs13"))
return img, plotLink
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 plotBarGraph(identification='', RISet='', vals=None, type="name"):
this_identification = "unnamed trait"
if identification:
this_identification = identification
if type=="rank":
dataXZ = vals[:]
dataXZ.sort(webqtlUtil.cmpOrder)
title='%s' % this_identification
else:
dataXZ = vals[:]
title='%s' % this_identification
tvals = []
tnames = []
tvars = []
for i in range(len(dataXZ)):
tvals.append(dataXZ[i][1])
tnames.append(webqtlUtil.genShortStrainName(RISet=RISet, input_strainName=dataXZ[i][0]))
tvars.append(dataXZ[i][2])
nnStrain = len(tnames)
sLabel = 1
###determine bar width and space width
if nnStrain < 20:
sw = 4
elif nnStrain < 40:
sw = 3
else:
sw = 2
### 700 is the default plot width minus Xoffsets for 40 strains
defaultWidth = 650
if nnStrain > 40:
defaultWidth += (nnStrain-40)*10
defaultOffset = 100
bw = int(0.5+(defaultWidth - (nnStrain-1.0)*sw)/nnStrain)
if bw < 10:
bw = 10
plotWidth = (nnStrain-1)*sw + nnStrain*bw + defaultOffset
plotHeight = 500
#print [plotWidth, plotHeight, bw, sw, nnStrain]
c = pid.PILCanvas(size=(plotWidth,plotHeight))
Plot.plotBarText(c, tvals, tnames, variance=tvars, YLabel='Value', title=title, sLabel = sLabel, barSpace = sw)
filename= webqtlUtil.genRandStr("Bar_")
c.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))
if type(pearsonEigenVectors[0][0]).__name__ == 'complex':
pearsonEigenVectors_0 = self.removeimag_array(values=pearsonEigenVectors[0])
else:
pearsonEigenVectors_0 = pearsonEigenVectors[0]
if type(pearsonEigenVectors[1][0]).__name__ == 'complex':
pearsonEigenVectors_1 = self.removeimag_array(values=pearsonEigenVectors[1])
else:
pearsonEigenVectors_1 = pearsonEigenVectors[1]
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 do_outliers(self):
values = [sample.value for sample in self.sample_list if sample.value != None]
upper_bound, lower_bound = Plot.find_outliers(values)
for sample in self.sample_list:
if sample.value:
if upper_bound and sample.value > upper_bound:
sample.outlier = True
elif lower_bound and sample.value < lower_bound:
sample.outlier = True
else:
sample.outlier = False
def do_outliers(self):
values = [sample.value for sample in self.sample_list
if sample.value is not None]
upper_bound, lower_bound = Plot.find_outliers(values)
for sample in self.sample_list:
if sample.value:
if upper_bound and sample.value > upper_bound:
sample.outlier = True
elif lower_bound and sample.value < lower_bound:
sample.outlier = True
else:
sample.outlier = False
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 drawGraph(self, canvas, data, cLength = 2500, offset= (80, 160, 60, 60), XLabel="QTL location (GMb)", YLabel="Gene location (GMb)"):
xLeftOffset, xRightOffset, yTopOffset, yBottomOffset = offset
plotWidth = canvas.size[0] - xLeftOffset - xRightOffset
plotHeight = canvas.size[1] - yTopOffset - yBottomOffset
#draw Frame
canvas.drawRect(plotWidth+xLeftOffset, plotHeight + yTopOffset, xLeftOffset, yTopOffset)
#draw Scale
i = 100
scaleFont=pid.Font(ttf="cour",size=11,bold=1)
while i < cLength:
yCoord = plotHeight + yTopOffset - plotHeight*i/cLength
canvas.drawLine(xLeftOffset,yCoord ,xLeftOffset-5, yCoord)
canvas.drawString("%d"% i, xLeftOffset -40, yCoord +5,font=scaleFont)
xCoord = xLeftOffset + plotWidth*i/cLength
canvas.drawLine(xCoord, plotHeight + yTopOffset ,xCoord, plotHeight + yTopOffset+5)
canvas.drawString("%d"% i, xCoord -10, plotHeight + yTopOffset+15,font=scaleFont)
i += 100
#draw Points
finecolors = Plot.colorSpectrum(300)
finecolors.reverse()
for item in data:
_pvalue = item[-1]
try:
_idx = int((-math.log10(_pvalue))*300/6.0) # XZ, 09/11/2008: add module name
_color = finecolors[_idx]
except:
_color = finecolors[-1]
canvas.drawCross(xLeftOffset + plotWidth*item[0]/cLength, plotHeight + yTopOffset - plotHeight*item[1]/cLength, color=_color,size=3)
#draw grid / always draw grid
if 1: #self.grid == "on":
for key in self.mouseChrLengthDict.keys():
length = self.mouseChrLengthDict[key]
if length != 0:
yCoord = plotHeight + yTopOffset - plotHeight*length/cLength
canvas.drawLine(xLeftOffset,yCoord ,xLeftOffset+plotWidth, yCoord, color=pid.lightgrey)
xCoord = xLeftOffset + plotWidth*length/cLength
canvas.drawLine(xCoord, plotHeight + yTopOffset ,xCoord, yTopOffset, color=pid.lightgrey)
#draw spectrum
i = 0
j = 0
middleoffsetX = 40
labelFont=pid.Font(ttf="tahoma",size=12,bold=0)
for dcolor in finecolors:
canvas.drawLine(xLeftOffset+ plotWidth + middleoffsetX -15 , plotHeight + yTopOffset - i, \
xLeftOffset+ plotWidth + middleoffsetX+15 , plotHeight + yTopOffset - i, color=dcolor)
if i % 50 == 0:
canvas.drawLine(xLeftOffset+ plotWidth +middleoffsetX+15 ,plotHeight + yTopOffset - i, \
xLeftOffset+ plotWidth +middleoffsetX+20,plotHeight + yTopOffset - i, color=pid.black)
canvas.drawString("%1.1f" % -j , xLeftOffset+ plotWidth +middleoffsetX+25 ,plotHeight + yTopOffset - i+5, font = labelFont)
j += 1
i += 1
canvas.drawLine(xLeftOffset+ plotWidth +middleoffsetX+15 ,plotHeight + yTopOffset - i+1, \
xLeftOffset+ plotWidth +middleoffsetX+20,plotHeight + yTopOffset - i+1, color=pid.black)
canvas.drawString("%1.1f" % -j , xLeftOffset+ plotWidth +middleoffsetX+25 ,plotHeight + yTopOffset - i+6, font = labelFont)
labelFont=pid.Font(ttf="tahoma",size=14,bold=1)
canvas.drawString("Log(pValue)" , xLeftOffset+ plotWidth +middleoffsetX+60 ,plotHeight + yTopOffset - 100, font = labelFont, angle =90)
labelFont=pid.Font(ttf="verdana",size=18,bold=0)
canvas.drawString(XLabel, xLeftOffset + (plotWidth -canvas.stringWidth(XLabel,font=labelFont))/2.0, plotHeight + yTopOffset +40, color=pid.blue, font=labelFont)
canvas.drawString(YLabel,xLeftOffset-60, plotHeight + yTopOffset-(plotHeight -canvas.stringWidth(YLabel,font=labelFont))/2.0, color=pid.blue, font=labelFont, angle =90)
return
def drawSVG(self, data, cLength = 2500, offset= (80, 160, 60, 60), size=(1280,880),
XLabel="Marker GMb", YLabel="Transcript GMb"):
entities = {
"colorText" : "fill:darkblue;",
"strokeText" : ";stroke:none;stroke-width:0;",
"allText" : "font-family:Helvetica;",
"titleText" : "font-size:22;font-weight:bold;",
"subtitleText" : "font-size:18;font-weight:bold;",
"headlineText" : "font-size:14;font-weight:bold;",
"normalText" : "font-size:12;",
"legendText" : "font-size:11;text-anchor:end;",
"valuesText" : "font-size:12;",
"boldValuesText" : "font-size:12;font-weight:bold;",
"smallText" : "font-size:10;",
"vText" : "writing-mode:tb-rl",
"rightText" : "text-anchor:end;",
"middleText" : "text-anchor:middle;",
"bezgrenzstyle" : "fill:none;stroke:#11A0FF;stroke-width:40;stroke-antialiasing:true;",
"rectstyle" : "fill:lightblue;stroke:none;opacity:0.2;",
"fillUnbebaut" : "fill:#CCFFD4;stroke:none;",
"fillNodata" : "fill:#E7E7E7;stroke:black;stroke-width:2;stroke-antialiasing:true;",
"fillNodataLegend" : "fill:#E7E7E7;stroke:black;stroke-width:0.5;stroke-antialiasing:true;",
"grundzeitstyle" : "fill:none;stroke:#E00004;stroke-width:60;stroke-antialiasing:true;",
"bezgrenzstyle" : "fill:none;stroke:#11A0FF;stroke-width:40;stroke-antialiasing:true;",
"mapAuthor" : "A. Neumann",
}
cWidth, cHeight = size
canvasSVG = svg.drawing(entities) #create a drawing
drawSpace=svg.svg((0, 0, cWidth, cHeight), cWidth, cHeight, xml__space="preserve",
zoomAndPan="disable", onload="initMap(evt);",
xmlns__a3="http://ns.adobe.com/AdobeSVGViewerExtensions/3.0/",
a3__scriptImplementation="Adobe") #create a svg drawingspace
canvasds=svg.description('Genome Graph') #define a description
drawSpace.addElement(canvasds) #add the description to the svg
#need to be modified or deleted
xLeftOffset, xRightOffset, yTopOffset, yBottomOffset = offset
plotWidth = cWidth - xLeftOffset - xRightOffset
plotHeight = cHeight - yTopOffset - yBottomOffset
drawSpace.addElement(svg.script("", language="javascript", xlink__href="/javascript/svg.js"))
#add defs
defs = svg.defs()
symbol1= svg.symbol(id="magnifyer", overflow="visible",
style="fill:white;stroke:orange;stroke-width:2;")
symbol1.addElement(svg.line(0, 0, -8, 20))
symbol1.addElement(svg.circle(0, 0, 8))
symbol1.addElement(svg.line(-4, 0, 4, 0, style="stroke:orange;stroke-width:2;"))
defs.addElement(symbol1)
symbol2= svg.symbol(id="magnifyerZoomIn",overflow="visible")
symbol2.addElement(svg.use(link="#magnifyer", id="zoomIn"))
symbol2.addElement(svg.line(0, -4, 0, 4, style="stroke:orange;stroke-width:2;"))
defs.addElement(symbol2)
drawSpace.addElement(defs)
symbol3= svg.symbol(id="msgbox", overflow="visible",
style="fill:white;stroke:orange;stroke-width:1;opacity:0.8;")
symbol3.addElement(svg.rect(-80, -190, 300, 150, rx=10, ry=10))
symbol3.addElement(svg.line(21, -40, 58, -40, style="stroke:white;"))
symbol3.addElement(svg.polyline([[20, -40], [0, 0], [60, -40]]))
symbol3.addElement(svg.text(-60, -160, "ProbeSet ", style="&colorText; &allText; &subtitleText; &strokeText;"))
symbol3.addElement(svg.text(-60, -125, "Marker ", style="&colorText; &allText; &subtitleText; &strokeText;"))
symbol3.addElement(svg.text(-60, -90, "LRS ", style="&colorText; &allText; &subtitleText; &strokeText;"))
symbol3.addElement(svg.text(-60, -55, "P value ", style="&colorText; &allText; &subtitleText; &strokeText;"))
defs.addElement(symbol3)
g = svg.group("title")
g.addElement(svg.text(cWidth-40, 30, "Genome Graph", style="&colorText; &allText; &titleText; &rightText;"))
g.addElement(svg.text(cWidth-40, 50, "Whole Transcriptome Mapping", style="&colorText; &allText; &subtitleText; &rightText;"))
drawSpace.addElement(g)
#draw Main display area border
mainSquare = cHeight-60
cordZOOM = 10
drawSpace.addElement(svg.rect(8, 8, mainSquare+4, mainSquare+4,'none',"orange",0.5, rx="5", ry="5"))
drawSpace.addElement(svg.text(10+mainSquare/2, 40+mainSquare,'Marker GMb',
style="&colorText; &allText; &titleText; &middleText;", id="XLabel"))
drawSpace.addElement(svg.text(mainSquare + 80, 10+mainSquare/2,'Transcript GMb',
style="&colorText; &allText; &titleText; &middleText; &vText;", id="YLabel"))
#draw overview display area
drawSpace.addElement(svg.rect(cWidth-40-260, 60, 260, 260,'none',"orange",0.5, rx="5", ry="5"))
drawSpaceThumb= svg.svg(id="overviewPlot",x=cWidth-40-260,y="60",width="260",
height="260",viewBox=(0, 0, mainSquare*cordZOOM, mainSquare*cordZOOM))
g = svg.group(style="&bezgrenzstyle;")
g.addElement(svg.use("#grid"))
drawSpaceThumb.addElement(g)
drawSpaceThumb.addElement(svg.rect(id="overviewRect",style="&rectstyle;",
x="0",y="0",width=mainSquare*cordZOOM,height=mainSquare*cordZOOM,
onmouseover="statusChange('click and drag rectangle to change extent');",
onmousedown="beginPan(evt);", onmousemove="doPan(evt);",
onmouseup="endPan();", onmouseout="endPan();"))
drawSpace.addElement(drawSpaceThumb)
#draw navigator
g = svg.group(id="navigatorElements")
g.addElement(svg.use("#magnifyerZoomIn", id="zoomIn", transform="translate(%d,350)" % (cWidth-40-130-20),
onmouseover="magnify(evt,1.3,'in');", onmouseout="magnify(evt,1,'in');", onclick="zoomIt('in');"))
g.addElement(svg.use("#magnifyer", id="zoomOut", transform="translate(%d,350)" % (cWidth-40-130+20),
onmouseover="magnify(evt,1.3,'out');",onmouseout="magnify(evt,1,'out');", onclick="zoomIt('out');"))
drawSpace.addElement(g)
g = svg.group(id="statusBar")
g.addElement(svg.text(cWidth-40-260, 360, "ZOOM: 100%", style="fill:orange; font-size:14;", id="zoomValueObj"))
g.addElement(svg.text(cWidth-40-260, 380, "Status:", style="&colorText; &allText; &smallText;"))
g.addElement(svg.text(cWidth-40-260, 395, "Loading Plot", style="&colorText; &allText; &smallText;", id="statusText"))
drawSpace.addElement(g)
#draw main display area
drawSpaceMain= svg.svg((0, 0, mainSquare*cordZOOM, mainSquare*cordZOOM), mainSquare, mainSquare,
id="mainPlot",x="10",y="10")
mPlotWidth = mPlotHeight = 0.8*mainSquare*cordZOOM
drawSpaceMain.addElement(svg.rect(mainSquare*cordZOOM*0.1, mainSquare*cordZOOM*0.1, mPlotWidth, mPlotHeight,style="fill:white",
onmousemove="showChr(evt);", onmouseover="showChr(evt);", onmouseout="showNoChr(evt);"))
#draw grid
g = svg.group("grid", style="stroke:lightblue;stroke-width:3",
transform="translate(%d,%d)" % (mainSquare*cordZOOM*0.1, mainSquare*cordZOOM*0.1))
if 1: #self.grid == "on":
js = []
for key in self.mouseChrLengthDict.keys():
length = self.mouseChrLengthDict[key]
js.append(mPlotWidth*length/cLength)
if length != 0:
yCoord = mPlotHeight*(1.0-length/cLength)
l = svg.line(0,yCoord ,mPlotWidth, yCoord)
g.addElement(l)
xCoord = mPlotWidth*length/cLength
l = svg.line(xCoord, 0 ,xCoord, mPlotHeight)
g.addElement(l)
js.sort()
drawSpace.addElement(svg.script("",language="javascript", cdata="var openURL=\"%s\";\nvar chrLength=%s;\n" % (self.openURL, js)))
g.addElement(svg.rect(0, 0, mPlotWidth, mPlotHeight,'none','black',10))
drawSpaceMain.addElement(g)
#draw Scale
g = svg.group("scale", style="stroke:black;stroke-width:0",
transform="translate(%d,%d)" % (mainSquare*cordZOOM*0.1, mainSquare*cordZOOM*0.1))
i = 100
scaleFontSize = 11*cordZOOM
while i < cLength:
yCoord = mPlotHeight - mPlotHeight*i/cLength
l = svg.line(0,yCoord ,-5*cordZOOM, yCoord)
g.addElement(l)
t = svg.text(-40*cordZOOM, yCoord +5*cordZOOM, "%d"% i, 100, "verdana") # coordinate tag Y
g.addElement(t)
xCoord = mPlotWidth*i/cLength
l = svg.line(xCoord, mPlotHeight, xCoord, mPlotHeight+5*cordZOOM)
g.addElement(l)
if i%200 == 0:
t = svg.text(xCoord, mPlotHeight+10*cordZOOM, "%d"% i, 100, "verdana") # coordinate tag X
g.addElement(t)
i += 100
drawSpaceMain.addElement(g)
#draw Points
finecolors = Plot.colorSpectrumSVG(12)
finecolors.reverse()
g = preColor = ""
for item in data:
_probeset, _chr, _Mb, _marker, _pvalue = item[2:]
try:
_idx = int((-math.log10(_pvalue))*12/6.0) # add module name
_color = finecolors[_idx]
except:
_color = finecolors[-1]
if _color != preColor:
preColor = _color
if g:
drawSpaceMain.addElement(g)
g = svg.group("points", style="stroke:%s;stroke-width:5" % _color,
transform="translate(%d,%d)" % (mainSquare*cordZOOM*0.1, mainSquare*cordZOOM*0.1),
onmouseover="mvMsgBox(evt);", onmouseout="hdMsgBox();", onmousedown="openPage(evt);")
else:
pass
px = mPlotWidth*item[0]/cLength
py = mPlotHeight*(1.0-item[1]/cLength)
l = svg.line("%2.1f" % (px-3*cordZOOM), "%2.1f" % py, "%2.1f" % (px+3*cordZOOM), "%2.1f" % py, ps=_probeset, mk=_marker)
g.addElement(l)
drawSpaceMain.addElement(g)
"""
#draw spectrum
i = 0
j = 0
middleoffsetX = 40
labelFont=pid.Font(ttf="tahoma",size=12,bold=0)
for dcolor in finecolors:
drawSpace.drawLine(xLeftOffset+ plotWidth + middleoffsetX -15 , plotHeight + yTopOffset - i, \
xLeftOffset+ plotWidth + middleoffsetX+15 , plotHeight + yTopOffset - i, color=dcolor)
if i % 50 == 0:
drawSpace.drawLine(xLeftOffset+ plotWidth +middleoffsetX+15 ,plotHeight + yTopOffset - i, \
xLeftOffset+ plotWidth +middleoffsetX+20,plotHeight + yTopOffset - i, color=pid.black)
drawSpace.drawString("%1.1f" % -j , xLeftOffset+ plotWidth +middleoffsetX+25 ,plotHeight + yTopOffset - i+5, font = labelFont)
j += 1
i += 1
drawSpace.drawLine(xLeftOffset+ plotWidth +middleoffsetX+15 ,plotHeight + yTopOffset - i+1, \
xLeftOffset+ plotWidth +middleoffsetX+20,plotHeight + yTopOffset - i+1, color=pid.black)
drawSpace.drawString("%1.1f" % -j , xLeftOffset+ plotWidth +middleoffsetX+25 ,plotHeight + yTopOffset - i+6, font = labelFont)
labelFont=pid.Font(ttf="tahoma",size=14,bold=1)
drawSpace.drawString("Log(pValue)" , xLeftOffset+ plotWidth +middleoffsetX+60 ,plotHeight + yTopOffset - 100, font = labelFont, angle =90)
labelFont=pid.Font(ttf="verdana",size=18,bold=0)
drawSpace.drawString(XLabel, xLeftOffset + (plotWidth -drawSpace.stringWidth(XLabel,font=labelFont))/2.0, plotHeight + yTopOffset +40, color=pid.blue, font=labelFont)
drawSpace.drawString(YLabel,xLeftOffset-60, plotHeight + yTopOffset-(plotHeight -drawSpace.stringWidth(YLabel,font=labelFont))/2.0, color=pid.blue, font=labelFont, angle =90)
"""
drawSpace.addElement(drawSpaceMain)
g= svg.group(id="dispBox", overflow="visible",
style="fill:white;stroke:orange;stroke-width:1;opacity:0.85;",
transform="translate(%d,650)" % (cWidth-40-300), visibility="hidden")
g.addElement(svg.rect(-80, -190, 300, 150, rx=10, ry=10))
g.addElement(svg.line(21, -40, 58, -40, style="stroke:white;"))
g.addElement(svg.polyline([[20, -40], [0, 0], [60, -40]]))
g.addElement(svg.text(-60, -160, "ProbeSet ", style="&colorText; &allText; &subtitleText; &strokeText;", id="_probeset"))
g.addElement(svg.text(-60, -125, "Marker ", style="&colorText; &allText; &subtitleText; &strokeText;", id="_marker"))
drawSpace.addElement(g)
canvasSVG.setSVG(drawSpace) #set the svg of the drawing to the svg
return canvasSVG
def __init__(self, fd):
templatePage.__init__(self, fd)
self.initializeDisplayParameters(fd)
if not fd.genotype:
fd.readGenotype()
mdpchoice = None
strainlist = fd.strainlist
fd.readData()
if not self.openMysql():
return
isSampleCorr = 1
isTissueCorr = 0
TD_LR = HT.TD(colspan=2, height=200, width="100%", bgColor="#eeeeee", align="left", wrap="off")
dataX = []
dataY = []
dataZ = [] # shortname
fullTissueName = []
xlabel = ""
ylabel = ""
if isSampleCorr:
plotHeading = HT.Paragraph("Sample Correlation Scatterplot")
plotHeading.__setattr__("class", "title")
# XZ: retrieve trait 1 info, Y axis
trait1_data = [] # trait 1 data
trait1Url = ""
try:
Trait1 = webqtlTrait(db=self.database, name=self.ProbeSetID, cellid=self.CellID, cursor=self.cursor)
Trait1.retrieveInfo()
Trait1.retrieveData()
except:
heading = "Retrieve Data"
detail = ["The database you just requested has not been established yet."]
self.error(heading=heading, detail=detail)
return
trait1_data = Trait1.exportData(strainlist)
trait1Url = Trait1.genHTML(dispFromDatabase=1)
ylabel = "%s : %s" % (Trait1.db.shortname, Trait1.name)
if Trait1.cellid:
ylabel += " : " + Trait1.cellid
# XZ, retrieve trait 2 info, X axis
trait2_data = [] # trait 2 data
trait2Url = ""
try:
Trait2 = webqtlTrait(db=self.database2, name=self.ProbeSetID2, cellid=self.CellID2, cursor=self.cursor)
Trait2.retrieveInfo()
Trait2.retrieveData()
except:
heading = "Retrieve Data"
detail = ["The database you just requested has not been established yet."]
self.error(heading=heading, detail=detail)
return
trait2_data = Trait2.exportData(strainlist)
trait2Url = Trait2.genHTML(dispFromDatabase=1)
xlabel = "%s : %s" % (Trait2.db.shortname, Trait2.name)
if Trait2.cellid:
xlabel += " : " + Trait2.cellid
for strain in Trait1.data.keys():
if Trait2.data.has_key(strain):
dataX.append(Trait2.data[strain].val)
dataY.append(Trait1.data[strain].val)
if self.showstrains:
dataZ.append(webqtlUtil.genShortStrainName(RISet=fd.RISet, input_strainName=strain))
# XZ: We have gotten all data for both traits.
if len(dataX) >= self.corrMinInformative:
if self.rankOrder == 0:
rankPrimary = 0
rankSecondary = 1
else:
rankPrimary = 1
rankSecondary = 0
lineColor = self.setLineColor()
symbolColor = self.setSymbolColor()
idColor = self.setIdColor()
c = pid.PILCanvas(size=(self.plotSize, self.plotSize * 0.90))
data_coordinate = Plot.plotXY(
canvas=c,
dataX=dataX,
dataY=dataY,
rank=rankPrimary,
dataLabel=dataZ,
labelColor=pid.black,
lineSize=self.lineSize,
lineColor=lineColor,
idColor=idColor,
idFont=self.idFont,
idSize=self.idSize,
symbolColor=symbolColor,
symbolType=self.symbol,
filled=self.filled,
symbolSize=self.symbolSize,
XLabel=xlabel,
connectdot=0,
YLabel=ylabel,
title="",
fitcurve=self.showline,
displayR=1,
offset=(90, self.plotSize / 20, self.plotSize / 10, 90),
showLabel=self.showIdentifiers,
)
if rankPrimary == 1:
dataXlabel, dataYlabel = webqtlUtil.calRank(xVals=dataX, yVals=dataY, N=len(dataX))
else:
dataXlabel, dataYlabel = dataX, dataY
gifmap1 = HT.Map(name="CorrelationPlotImageMap1")
for i, item in enumerate(data_coordinate):
one_rect_coordinate = "%d, %d, %d, %d" % (item[0] - 5, item[1] - 5, item[0] + 5, item[1] + 5)
if isTissueCorr:
one_rect_title = "%s (%s, %s)" % (fullTissueName[i], dataXlabel[i], dataYlabel[i])
else:
one_rect_title = "%s (%s, %s)" % (dataZ[i], dataXlabel[i], dataYlabel[i])
gifmap1.areas.append(HT.Area(shape="rect", coords=one_rect_coordinate, title=one_rect_title))
filename = webqtlUtil.genRandStr("XY_")
c.save(webqtlConfig.IMGDIR + filename, format="gif")
img1 = HT.Image("/image/" + filename + ".gif", border=0, usemap="#CorrelationPlotImageMap1")
mainForm_1 = 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": "_",
"RISet": fd.RISet,
"ProbeSetID2": "_",
"database2": "_",
"CellID2": "_",
"allstrainlist": string.join(fd.strainlist, " "),
"traitList": fd.formdata.getvalue("traitList"),
}
if fd.incparentsf1:
hddn["incparentsf1"] = "ON"
for key in hddn.keys():
mainForm_1.append(HT.Input(name=key, value=hddn[key], type="hidden"))
if isSampleCorr:
mainForm_1.append(
HT.P(),
HT.Blockquote(
HT.Strong("X axis:"),
HT.Blockquote(trait2Url),
HT.Strong("Y axis:"),
HT.Blockquote(trait1Url),
style="width: %spx;" % self.plotSize,
wrap="hard",
),
)
graphForm = HT.Form(
cgi=os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE),
name="MDP_Form",
submit=HT.Input(type="hidden"),
)
graph_hddn = self.setHiddenParameters(fd, rankPrimary)
webqtlUtil.exportData(
graph_hddn, fd.allTraitData
) # XZ: This is necessary to replot with different groups of strains
for key in graph_hddn.keys():
graphForm.append(HT.Input(name=key, value=graph_hddn[key], type="hidden"))
options = self.createOptionsMenu(fd, mdpchoice)
if self.showOptions == "0":
showOptionsButton = HT.Input(
type="button",
name="optionsButton",
value="Hide Options",
onClick="showHideOptions();",
Class="button",
)
else:
showOptionsButton = HT.Input(
type="button",
name="optionsButton",
value="Show Options",
onClick="showHideOptions();",
Class="button",
)
# updated by NL: 12-07-2011 add variables for tissue abbreviation page
if isTissueCorr:
graphForm.append(HT.Input(name="shortTissueName", value="", type="hidden"))
graphForm.append(HT.Input(name="fullTissueName", value="", type="hidden"))
shortTissueNameStr = string.join(dataZ, ",")
fullTissueNameStr = string.join(fullTissueName, ",")
tissueAbbrButton = HT.Input(
type="button",
name="tissueAbbrButton",
value="Show Abbreviations",
onClick="showTissueAbbr('MDP_Form','%s','%s')" % (shortTissueNameStr, fullTissueNameStr),
Class="button",
)
graphForm.append(showOptionsButton, " ", tissueAbbrButton, HT.BR(), HT.BR())
else:
graphForm.append(showOptionsButton, HT.BR(), HT.BR())
graphForm.append(options, HT.BR())
graphForm.append(HT.HR(), HT.BR(), HT.P())
TD_LR.append(plotHeading, HT.BR(), graphForm, HT.BR(), gifmap1, HT.P(), img1, HT.P(), mainForm_1)
TD_LR.append(HT.BR(), HT.HR(color="grey", size=5, width="100%"))
c = pid.PILCanvas(size=(self.plotSize, self.plotSize * 0.90))
data_coordinate = Plot.plotXY(
canvas=c,
dataX=dataX,
dataY=dataY,
rank=rankSecondary,
dataLabel=dataZ,
labelColor=pid.black,
lineColor=lineColor,
lineSize=self.lineSize,
idColor=idColor,
idFont=self.idFont,
idSize=self.idSize,
symbolColor=symbolColor,
symbolType=self.symbol,
filled=self.filled,
symbolSize=self.symbolSize,
XLabel=xlabel,
connectdot=0,
YLabel=ylabel,
title="",
fitcurve=self.showline,
displayR=1,
offset=(90, self.plotSize / 20, self.plotSize / 10, 90),
showLabel=self.showIdentifiers,
)
if rankSecondary == 1:
dataXlabel, dataYlabel = webqtlUtil.calRank(xVals=dataX, yVals=dataY, N=len(dataX))
else:
dataXlabel, dataYlabel = dataX, dataY
gifmap2 = HT.Map(name="CorrelationPlotImageMap2")
for i, item in enumerate(data_coordinate):
one_rect_coordinate = "%d, %d, %d, %d" % (item[0] - 6, item[1] - 6, item[0] + 6, item[1] + 6)
if isTissueCorr:
one_rect_title = "%s (%s, %s)" % (fullTissueName[i], dataXlabel[i], dataYlabel[i])
else:
one_rect_title = "%s (%s, %s)" % (dataZ[i], dataXlabel[i], dataYlabel[i])
gifmap2.areas.append(HT.Area(shape="rect", coords=one_rect_coordinate, title=one_rect_title))
filename = webqtlUtil.genRandStr("XY_")
c.save(webqtlConfig.IMGDIR + filename, format="gif")
img2 = HT.Image("/image/" + filename + ".gif", border=0, usemap="#CorrelationPlotImageMap2")
mainForm_2 = HT.Form(
cgi=os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE),
enctype="multipart/form-data",
name="showDatabase2",
submit=HT.Input(type="hidden"),
)
hddn = {
"FormID": "showDatabase2",
"ProbeSetID": "_",
"database": "_",
"CellID": "_",
"RISet": fd.RISet,
"ProbeSetID2": "_",
"database2": "_",
"CellID2": "_",
"allstrainlist": string.join(fd.strainlist, " "),
"traitList": fd.formdata.getvalue("traitList"),
}
if fd.incparentsf1:
hddn["incparentsf1"] = "ON"
for key in hddn.keys():
mainForm_2.append(HT.Input(name=key, value=hddn[key], type="hidden"))
if isSampleCorr:
mainForm_2.append(
HT.P(),
HT.Blockquote(
HT.Strong("X axis:"),
HT.Blockquote(trait2Url),
HT.Strong("Y axis:"),
HT.Blockquote(trait1Url),
style="width:%spx;" % self.plotSize,
),
)
TD_LR.append(HT.BR(), HT.P())
TD_LR.append("\n", gifmap2, HT.P(), HT.P(), img2, HT.P(), mainForm_2)
self.dict["body"] = str(TD_LR)
else:
heading = "Correlation Plot"
detail = [
"Fewer than %d strain data were entered for %s data set. No statitical analysis has been attempted."
% (self.corrMinInformative, fd.RISet)
]
self.error(heading=heading, detail=detail)
return
def __init__(self, fd):
LRSFullThresh = 30
LRSInteractThresh = 25
maxPlotSize = 800
mainfmName = webqtlUtil.genRandStr("fm_")
templatePage.__init__(self, fd)
if not fd.genotype:
fd.readData()
##Remove F1 and Parents
fd.genotype = fd.genotype_1
plotType = fd.formdata.getvalue('plotType')
self.dict['title'] = '%s Plot' % plotType
main_title = HT.Paragraph("%s Plot" % plotType)
main_title.__setattr__("class","title")
interval1 = fd.formdata.getvalue('interval1')
interval2 = fd.formdata.getvalue('interval2')
flanka1, flanka2, chram = string.split(interval1)
flankb1, flankb2, chrbm = string.split(interval2)
traitValues = string.split(fd.formdata.getvalue('traitValues'), ',')
traitValues = map(webqtlUtil.StringAsFloat, traitValues)
traitStrains = string.split(fd.formdata.getvalue('traitStrains'), ',')
flankaGeno = []
flankbGeno = []
for chr in fd.genotype:
for locus in chr:
if locus.name in (flanka1, flankb1):
if locus.name == flanka1:
flankaGeno = locus.genotype[:]
else:
flankbGeno = locus.genotype[:]
if flankaGeno and flankbGeno:
break
flankaDict = {}
flankbDict = {}
for i in range(len(fd.genotype.prgy)):
flankaDict[fd.genotype.prgy[i]] = flankaGeno[i]
flankbDict[fd.genotype.prgy[i]] = flankbGeno[i]
BB = []
BD = []
DB = []
DD = []
iValues = []
for i in range(len(traitValues)):
if traitValues[i] != None:
iValues.append(traitValues[i])
thisstrain = traitStrains[i]
try:
a1 = flankaDict[thisstrain]
b1 = flankbDict[thisstrain]
except:
continue
if a1 == -1.0:
if b1 == -1.0:
BB.append((thisstrain, traitValues[i]))
elif b1 == 1.0:
BD.append((thisstrain, traitValues[i]))
elif a1 == 1.0:
if b1 == -1.0:
DB.append((thisstrain, traitValues[i]))
elif b1 == 1.0:
DD.append((thisstrain, traitValues[i]))
else:
pass
#print BB, BD, DB, DD, max(iValues), min(iValues)
plotHeight = 400
plotWidth = 600
xLeftOffset = 60
xRightOffset = 40
yTopOffset = 40
yBottomOffset = 60
canvasHeight = plotHeight + yTopOffset + yBottomOffset
canvasWidth = plotWidth + xLeftOffset + xRightOffset
canvas = pid.PILCanvas(size=(canvasWidth,canvasHeight))
XXX = [('Mat/Mat', BB), ('Mat/Pat', BD), ('Pat/Mat', DB), ('Pat/Pat', DD)]
XLabel = "Interval 1 / Interval 2"
if plotType == "Box":
Plot.plotBoxPlot(canvas, XXX, offset=(xLeftOffset, xRightOffset, yTopOffset, yBottomOffset), XLabel = XLabel)
else:
#Could be a separate function, but seems no other uses
max_Y = max(iValues)
min_Y = min(iValues)
scaleY = Plot.detScale(min_Y, max_Y)
Yll = scaleY[0]
Yur = scaleY[1]
nStep = scaleY[2]
stepY = (Yur - Yll)/nStep
stepYPixel = plotHeight/(nStep)
canvas.drawRect(plotWidth+xLeftOffset, plotHeight + yTopOffset, xLeftOffset, yTopOffset)
##draw Y Scale
YYY = Yll
YCoord = plotHeight + yTopOffset
scaleFont=pid.Font(ttf="cour",size=11,bold=1)
for i in range(nStep+1):
strY = Plot.cformat(d=YYY, rank=0)
YCoord = max(YCoord, yTopOffset)
canvas.drawLine(xLeftOffset,YCoord,xLeftOffset-5,YCoord)
canvas.drawString(strY, xLeftOffset -30,YCoord +5,font=scaleFont)
YYY += stepY
YCoord -= stepYPixel
##draw X Scale
stepX = plotWidth/len(XXX)
XCoord = xLeftOffset + 0.5*stepX
YCoord = plotHeight + yTopOffset
scaleFont = pid.Font(ttf="tahoma",size=12,bold=0)
labelFont = pid.Font(ttf="tahoma",size=13,bold=0)
for item in XXX:
itemname, itemvalue = item
canvas.drawLine(XCoord, YCoord,XCoord, YCoord+5, color=pid.black)
canvas.drawString(itemname, XCoord - canvas.stringWidth(itemname,font=labelFont)/2.0,YCoord +20,font=labelFont)
itemvalue.sort(webqtlUtil.cmpOrder2)
j = 0
for item2 in itemvalue:
tstrain, tvalue = item2
canvas.drawCross(XCoord, plotHeight + yTopOffset - (tvalue-Yll)*plotHeight/(Yur - Yll), color=pid.red,size=5)
if j % 2 == 0:
canvas.drawString(tstrain, XCoord+5, plotHeight + yTopOffset - \
(tvalue-Yll)*plotHeight/(Yur - Yll) +5, font=scaleFont, color=pid.blue)
else:
canvas.drawString(tstrain, XCoord-canvas.stringWidth(tstrain,font=scaleFont)-5, \
plotHeight + yTopOffset - (tvalue-Yll)*plotHeight/(Yur - Yll) +5, font=scaleFont, color=pid.blue)
j += 1
XCoord += stepX
labelFont=pid.Font(ttf="verdana",size=18,bold=0)
canvas.drawString(XLabel, xLeftOffset + (plotWidth -canvas.stringWidth(XLabel,font=labelFont))/2.0, YCoord +40, font=labelFont)
canvas.drawString("Value",xLeftOffset-40, YCoord-(plotHeight -canvas.stringWidth("Value",font=labelFont))/2.0, font=labelFont, angle =90)
filename= webqtlUtil.genRandStr("Cate_")
canvas.save(webqtlConfig.IMGDIR+filename, format='gif')
img=HT.Image('/image/'+filename+'.gif',border=0)
TD_LR = HT.TD(height=200,width="100%",bgColor='#eeeeee',valign='top')
TD_LR.append(main_title, HT.Center(img))#, traitValues , len(traitValues), traitStrains, len(traitStrains), len(fd.genotype.prgy))
#TD_LR.append(main_title, HT.BR(), flanka1, flanka2, chram, HT.BR(), flankb1, flankb2, chrbm)
self.dict['body'] = str(TD_LR)
def __init__(self, fd):
templatePage.__init__(self, fd)
if not fd.genotype:
fd.readGenotype()
strainlist2 = fd.strainlist
if fd.allstrainlist:
strainlist2 = fd.allstrainlist
fd.readData(strainlist2)
specialStrains = []
setStrains = []
for item in strainlist2:
if item not in fd.strainlist and item.find('F1') < 0:
specialStrains.append(item)
else:
setStrains.append(item)
specialStrains.sort()
#So called MDP Panel
if specialStrains:
specialStrains = fd.f1list+fd.parlist+specialStrains
self.plotType = fd.formdata.getvalue('ptype', '0')
plotStrains = strainlist2
if specialStrains:
if self.plotType == '1':
plotStrains = setStrains
if self.plotType == '2':
plotStrains = specialStrains
self.dict['title'] = 'Basic Statistics'
if not self.openMysql():
return
self.showstrains = 1
self.identification = "unnamed trait"
self.fullname = fd.formdata.getvalue('fullname', '')
if self.fullname:
self.Trait = webqtlTrait(fullname=self.fullname, cursor=self.cursor)
self.Trait.retrieveInfo()
else:
self.Trait = None
if fd.identification:
self.identification = fd.identification
self.dict['title'] = self.identification + ' / '+self.dict['title']
TD_LR = HT.TD(height=200,width="100%",bgColor='#eeeeee')
##should not display Variance, but cannot convert Variance to SE
#print plotStrains, fd.allTraitData.keys()
if len(fd.allTraitData) > 0:
vals=[]
InformData = []
for _strain in plotStrains:
if fd.allTraitData.has_key(_strain):
_val, _var = fd.allTraitData[_strain].val, fd.allTraitData[_strain].var
if _val != None:
vals.append([_strain, _val, _var])
InformData.append(_val)
if len(vals) >= self.plotMinInformative:
supertable2 = HT.TableLite(border=0, cellspacing=0, cellpadding=5,width="800")
staIntro1 = HT.Paragraph("The table and plots below list the basic statistical analysis result of trait",HT.Strong(" %s" % self.identification))
#####
#anova
#####
traitmean, traitmedian, traitvar, traitstdev, traitsem, N = reaper.anova(InformData)
TDStatis = HT.TD(width="360", valign="top")
tbl2 = HT.TableLite(cellpadding=5, cellspacing=0, Class="collap")
dataXZ = vals[:]
dataXZ.sort(self.cmpValue)
tbl2.append(HT.TR(HT.TD("Statistic",align="center", Class="fs14 fwb ffl b1 cw cbrb", width = 200),
HT.TD("Value", align="center", Class="fs14 fwb ffl b1 cw cbrb", width = 140)))
tbl2.append(HT.TR(HT.TD("N of Cases",align="center", Class="fs13 b1 cbw c222"),
HT.TD(N,nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
tbl2.append(HT.TR(HT.TD("Mean",align="center", Class="fs13 b1 cbw c222",nowrap="yes"),
HT.TD("%2.3f" % traitmean,nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
tbl2.append(HT.TR(HT.TD("Median",align="center", Class="fs13 b1 cbw c222",nowrap="yes"),
HT.TD("%2.3f" % traitmedian,nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
#tbl2.append(HT.TR(HT.TD("Variance",align="center", Class="fs13 b1 cbw c222",nowrap="yes"),
# HT.TD("%2.3f" % traitvar,nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
tbl2.append(HT.TR(HT.TD("SEM",align="center", Class="fs13 b1 cbw c222",nowrap="yes"),
HT.TD("%2.3f" % traitsem,nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
tbl2.append(HT.TR(HT.TD("SD",align="center", Class="fs13 b1 cbw c222",nowrap="yes"),
HT.TD("%2.3f" % traitstdev,nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
tbl2.append(HT.TR(HT.TD("Minimum",align="center", Class="fs13 b1 cbw c222",nowrap="yes"),
HT.TD("%s" % dataXZ[0][1],nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
tbl2.append(HT.TR(HT.TD("Maximum",align="center", Class="fs13 b1 cbw c222",nowrap="yes"),
HT.TD("%s" % dataXZ[-1][1],nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
if self.Trait and self.Trait.db.type == 'ProbeSet':
#IRQuest = HT.Href(text="Interquartile Range", url=webqtlConfig.glossaryfile +"#Interquartile",target="_blank", Class="fs14")
#IRQuest.append(HT.BR())
#IRQuest.append(" (fold difference)")
tbl2.append(HT.TR(HT.TD("Range (log2)",align="center", Class="fs13 b1 cbw c222",nowrap="yes"),
HT.TD("%2.3f" % (dataXZ[-1][1]-dataXZ[0][1]),nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
tbl2.append(HT.TR(HT.TD(HT.Span("Range (fold)"),align="center", Class="fs13 b1 cbw c222",nowrap="yes"),
HT.TD("%2.2f" % pow(2.0,(dataXZ[-1][1]-dataXZ[0][1])), nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
tbl2.append(HT.TR(HT.TD(HT.Span("Quartile Range",HT.BR()," (fold difference)"),align="center", Class="fs13 b1 cbw c222",nowrap="yes"),
HT.TD("%2.2f" % pow(2.0,(dataXZ[int((N-1)*3.0/4.0)][1]-dataXZ[int((N-1)/4.0)][1])), nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
# (Lei Yan)
# 2008/12/19
self.Trait.retrieveData()
#XZ, 04/01/2009: don't try to get H2 value for probe.
if self.Trait.cellid:
pass
else:
self.cursor.execute("SELECT DataId, h2 from ProbeSetXRef WHERE DataId = %d" % self.Trait.mysqlid)
dataid, heritability = self.cursor.fetchone()
if heritability:
tbl2.append(HT.TR(HT.TD(HT.Span("Heritability"),align="center", Class="fs13 b1 cbw c222",nowrap="yes"),HT.TD("%s" % heritability, nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
else:
tbl2.append(HT.TR(HT.TD(HT.Span("Heritability"),align="center", Class="fs13 b1 cbw c222",nowrap="yes"),HT.TD("NaN", nowrap="yes",align="center", Class="fs13 b1 cbw c222")))
# Lei Yan
# 2008/12/19
TDStatis.append(tbl2)
plotHeight = 220
plotWidth = 120
xLeftOffset = 60
xRightOffset = 25
yTopOffset = 20
yBottomOffset = 53
canvasHeight = plotHeight + yTopOffset + yBottomOffset
canvasWidth = plotWidth + xLeftOffset + xRightOffset
canvas = pid.PILCanvas(size=(canvasWidth,canvasHeight))
XXX = [('', InformData[:])]
Plot.plotBoxPlot(canvas, XXX, offset=(xLeftOffset, xRightOffset, yTopOffset, yBottomOffset), XLabel= "Trait")
filename= webqtlUtil.genRandStr("Box_")
canvas.save(webqtlConfig.IMGDIR+filename, format='gif')
img=HT.Image('/image/'+filename+'.gif',border=0)
#supertable2.append(HT.TR(HT.TD(staIntro1, colspan=3 )))
tb = HT.TableLite(border=0, cellspacing=0, cellpadding=0)
tb.append(HT.TR(HT.TD(img, align="left", style="border: 1px solid #999999; padding:0px;")))
supertable2.append(HT.TR(TDStatis, HT.TD(tb)))
dataXZ = vals[:]
tvals = []
tnames = []
tvars = []
for i in range(len(dataXZ)):
tvals.append(dataXZ[i][1])
tnames.append(webqtlUtil.genShortStrainName(fd, dataXZ[i][0]))
tvars.append(dataXZ[i][2])
nnStrain = len(tnames)
sLabel = 1
###determine bar width and space width
if nnStrain < 20:
sw = 4
elif nnStrain < 40:
sw = 3
else:
sw = 2
### 700 is the default plot width minus Xoffsets for 40 strains
defaultWidth = 650
if nnStrain > 40:
defaultWidth += (nnStrain-40)*10
defaultOffset = 100
bw = int(0.5+(defaultWidth - (nnStrain-1.0)*sw)/nnStrain)
if bw < 10:
bw = 10
plotWidth = (nnStrain-1)*sw + nnStrain*bw + defaultOffset
plotHeight = 500
#print [plotWidth, plotHeight, bw, sw, nnStrain]
c = pid.PILCanvas(size=(plotWidth,plotHeight))
Plot.plotBarText(c, tvals, tnames, variance=tvars, YLabel='Value', title='%s by Case (sorted by name)' % self.identification, sLabel = sLabel, barSpace = sw)
filename= webqtlUtil.genRandStr("Bar_")
c.save(webqtlConfig.IMGDIR+filename, format='gif')
img0=HT.Image('/image/'+filename+'.gif',border=0)
dataXZ = vals[:]
dataXZ.sort(self.cmpValue)
tvals = []
tnames = []
tvars = []
for i in range(len(dataXZ)):
tvals.append(dataXZ[i][1])
tnames.append(webqtlUtil.genShortStrainName(fd, dataXZ[i][0]))
tvars.append(dataXZ[i][2])
c = pid.PILCanvas(size=(plotWidth,plotHeight))
Plot.plotBarText(c, tvals, tnames, variance=tvars, YLabel='Value', title='%s by Case (ranked)' % self.identification, sLabel = sLabel, barSpace = sw)
filename= webqtlUtil.genRandStr("Bar_")
c.save(webqtlConfig.IMGDIR+filename, format='gif')
img1=HT.Image('/image/'+filename+'.gif',border=0)
# Lei Yan
# 05/18/2009
# report
title = HT.Paragraph('REPORT on the variation of Shh (or PCA Composite Trait XXXX) (sonic hedgehog) in the (insert Data set name) of (insert Species informal name, e.g., Mouse, Rat, Human, Barley, Arabidopsis)', Class="title")
header = HT.Paragraph('''This report was generated by GeneNetwork on May 11, 2009, at 11.20 AM using the Basic Statistics module (v 1.0) and data from the Hippocampus Consortium M430v2 (Jun06) PDNN data set. For more details and updates on this data set please link to URL:get Basic Statistics''')
hr = HT.HR()
p1 = HT.Paragraph('''Trait values for Shh were taken from the (insert Database name, Hippocampus Consortium M430v2 (Jun06) PDNN). GeneNetwork contains data for NN (e.g., 99) cases. In general, data are averages for each case. A summary of mean, median, and the range of these data are provided in Table 1 and in the box plot (Figure 1). Data for individual cases are provided in Figure 2A and 2B, often with error bars (SEM). ''')
p2 = HT.Paragraph('''Trait values for Shh range 5.1-fold: from a low of 8.2 (please round value) in 129S1/SvImJ to a high of 10.6 (please round value) in BXD9. The interquartile range (the difference between values closest to the 25% and 75% levels) is a more modest 1.8-fold. The mean value is XX. ''')
t1 = HT.Paragraph('''Table 1. Summary of Shh data from the Hippocampus Consortium M430v2 (june06) PDNN data set''')
f1 = HT.Paragraph('''Figure 1. ''')
f1.append(HT.Href(text="Box plot", url="http://davidmlane.com/hyperstat/A37797.html", target="_blank", Class="fs14"))
f1.append(HT.Text(''' of Shh data from the Hippocampus Consortium M430v2 (june06) PDNN data set'''))
f2A = HT.Paragraph('''Figure 2A: Bar chart of Shh data ordered by case from the Hippocampus Consortium M430v2 (june06) PDNN data set''')
f2B = HT.Paragraph('''Figure 2B: Bar chart of Shh values ordered by from the Hippocampus Consortium M430v2 (june06) PDNN data set''')
TD_LR.append(HT.Blockquote(title, HT.P(), header, hr, p1, HT.P(), p2, HT.P(), supertable2, t1, f1, HT.P(), img0, f2A, HT.P(), img1, f2B))
self.dict['body'] = str(TD_LR)
else:
heading = "Basic Statistics"
detail = ['Fewer than %d case data were entered for %s data set. No statitical analysis has been attempted.' % (self.plotMinInformative, fd.RISet)]
self.error(heading=heading,detail=detail)
return
else:
heading = "Basic Statistics"
detail = ['Empty data set, please check your data.']
self.error(heading=heading,detail=detail)
return
def __init__(self, fd):
LRSFullThresh = 30
LRSInteractThresh = 25
templatePage.__init__(self, fd)
if not fd.genotype:
fd.readData()
incVars = 0
_genotype = fd.genotype_1
_strains, _vals, _vars, N = fd.informativeStrains(_genotype.prgy, incVars)
self.dict['title'] = 'Pair-Scan Plot'
if not self.openMysql():
return
iPermuCheck = fd.formdata.getvalue('directPermuCheckbox')
try:
graphtype = int(fd.formdata.getvalue('graphtype'))
except:
graphtype = 1
try:
graphsort = int(fd.formdata.getvalue('graphSort'))
except:
graphsort = 1
try:
returnIntervalPairNum = int(fd.formdata.getvalue('pairScanReturn'))
except:
returnIntervalPairNum = 50
pairIntro = HT.Blockquote("The graph below displays pair-scan results for the trait ",HT.Strong(" %s" % fd.identification))
if not graphsort:
tblIntro = HT.Blockquote('This table lists LRS scores for the top %d pairs of intervals (Interval 1 on the left and Interval 2 on the right). Pairs are sorted by the "LRS Full" column. Both intervals are defined by proximal and distal markers that flank the single best position.' % returnIntervalPairNum)
else:
tblIntro = HT.Blockquote('This table lists LRS scores for the top %d pairs of intervals (Interval 1 on the left and Interval 2 on the right). Pairs are sorted by the "LRS Interaction" column. Both intervals are defined by proximal and distal markers that flank the single best position.' % returnIntervalPairNum)
try:
thisTrait = webqtlTrait(fullname=fd.formdata.getvalue("fullname"), cursor=self.cursor)
pairIntro.append(' from the database ' , thisTrait.db.genHTML())
except:
pass
pairIntro.append('. The upper left half of the plot highlights any epistatic interactions (corresponding to the column labeled "LRS Interact"). In contrast, the lower right half provides a summary of LRS of the full model, representing cumulative effects of linear and non-linear terms (column labeled "LRS Full"). The WebQTL implementation of the scan for 2-locus epistatic interactions is based on the DIRECT global optimization algorithm developed by ',HT.Href(text ="Ljungberg",url='http://user.it.uu.se/~kl/qtl_software.html',target="_blank", Class = "fs14 fwn"),', Holmgren, and Carlborg (',HT.Href(text = "2004",url='http://bioinformatics.oupjournals.org/cgi/content/abstract/bth175?ijkey=21Pp0pgOuBL6Q&keytype=ref', Class = "fs14 fwn"),').')
main_title = HT.Paragraph("Pair-Scan Results: An Analysis of Epistatic Interactions")
main_title.__setattr__("class","title")
subtitle1 = HT.Paragraph("Pair-Scan Graph")
subtitle3 = HT.Paragraph("Pair-Scan Top LRS")
subtitle1.__setattr__("class","subtitle")
subtitle3.__setattr__("class","subtitle")
self.identification = "unnamed trait"
if fd.identification:
self.identification = fd.identification
self.dict['title'] = self.identification + ' / '+self.dict['title']
#####################################
#
# Remove the Parents & F1 data
#
#####################################
if _vals:
if len(_vals) > webqtlConfig.KMININFORMATIVE:
ResultFull = []
ResultInteract = []
ResultAdd = []
#permutation test
subtitle2 = ''
permuTbl = ''
permuIntro = ''
if iPermuCheck:
subtitle2 = HT.Paragraph("Pair-Scan Permutation Results")
subtitle2.__setattr__("class","subtitle")
permuIntro = HT.Blockquote("Phenotypes were randomly permuted 500 times among strains or individuals and reanalyzed using the pair-scan algorithm. We extracted the single highest LRS for the full model for each of these permuted data sets. The histograms of these highest LRS values provide an empirical way to estimate the probability of obtaining an LRS above suggestive or significant thresholds.")
prtmuTblIntro1 = HT.Paragraph("The following table gives threshold values for Suggestive (P=0.63) and Significant associations (P=0.05) defined by Lander & Kruglyak and for the slightly more stringent P=0.01 level. (The Highly Significant level of Lander & Kruglyak corresponds to P=0.001 and cannot be estimated with 500 permutations.)")
prtmuTblIntro2 = HT.Paragraph("If the full model exceeds the permutation-based Significant threshold, then different models for those locations can be tested by conventional chi-square tests at P<0.01. Interaction is significant if LRS Interact exceeds 6.64 for RI strains or 13.28 for an F2. If interaction is not significant, the two-QTL model is better than a one-QTL model if LRS Additive exceeds LRS 1 or LRS 2 by 6.64 for RI strains or 9.21 for an F2.")
ResultFull, ResultInteract, ResultAdd = direct.permu(webqtlConfig.GENODIR, _vals, _strains, fd.RISet, 500) #XZ, 08/14/2008: add module name webqtlConfig
ResultFull.sort()
ResultInteract.sort()
ResultAdd.sort()
nPermuResult = len(ResultFull)
# draw Histogram
cFull = pid.PILCanvas(size=(400,300))
Plot.plotBar(cFull, ResultFull,XLabel='LRS',YLabel='Frequency',title=' Histogram of LRS Full')
#plotBar(cFull,10,10,390,290,ResultFull,XLabel='LRS',YLabel='Frequency',title=' Histogram of LRS Full')
filename= webqtlUtil.genRandStr("Pair_")
cFull.save(webqtlConfig.IMGDIR+filename, format='gif')
imgFull=HT.Image('/image/'+filename+'.gif',border=0,alt='Histogram of LRS Full')
superPermuTbl = HT.TableLite(border=0, cellspacing=0, cellpadding=0,bgcolor ='#999999')
permuTbl2 = HT.TableLite(border=0, cellspacing= 1, cellpadding=5)
permuTbl2.append(HT.TR(HT.TD(HT.Font('LRS', color = '#FFFFFF')), HT.TD(HT.Font('p = 0.63', color = '#FFFFFF'), width = 150, align='Center'), HT.TD(HT.Font('p = 0.05', color = '#FFFFFF'), width = 150, align='Center'), HT.TD(HT.Font('p = 0.01', color = '#FFFFFF'), width = 150, align='Center'),bgColor='royalblue'))
permuTbl2.append(HT.TR(HT.TD('Full'), HT.TD('%2.1f' % ResultFull[int(nPermuResult*0.37 -1)], align="Center"), HT.TD('%2.1f' % ResultFull[int(nPermuResult*0.95 -1)], align="Center"), HT.TD('%2.1f' % ResultFull[int(nPermuResult*0.99 -1)], align="Center"),bgColor="#eeeeee"))
superPermuTbl.append(HT.TD(HT.TD(permuTbl2)))
permuTbl1 = HT.TableLite(border=0, cellspacing= 0, cellpadding=5,width='100%')
permuTbl1.append(HT.TR(HT.TD(imgFull, align="Center", width = 410), HT.TD(prtmuTblIntro1, superPermuTbl, prtmuTblIntro2, width = 490)))
permuTbl = HT.Center(permuTbl1, HT.P())
#permuTbl.append(HT.TR(HT.TD(HT.BR(), 'LRS Full = %2.1f, ' % ResultFull[int(nPermuResult*0.37 -1)], 'LRS Full = %2.1f, ' % ResultFull[int(nPermuResult*0.95 -1)], 'LRS Full highly significant (p=0.001) = %2.1f, ' % ResultFull[int(nPermuResult*0.999 -1)] , HT.BR(), 'LRS Interact suggestive (p=0.63) = %2.1f, ' % ResultInteract[int(nPermuResult*0.37 -1)], 'LRS Interact significant (p=0.05) = %2.1f, ' % ResultInteract[int(nPermuResult*0.95 -1)], 'LRS Interact = %2.1f, ' % ResultInteract[int(nPermuResult*0.999 -1)] , HT.BR(),'LRS Additive suggestive (p=0.63) = %2.1f, ' % ResultAdd[int(nPermuResult*0.37 -1)], 'LRS Additive significant (p=0.05) = %2.1f, ' % ResultAdd[int(nPermuResult*0.95 -1)], 'LRS Additive highly significant (p=0.001) = %2.1f, ' % ResultAdd[int(nPermuResult*0.999 -1)], HT.BR(), 'Total number of permutation is %d' % nPermuResult, HT.BR(), HT.BR(),colspan=2)))
#tblIntro.append(HT.P(), HT.Center(permuTbl))
#print vals, strains, fd.RISet
d = direct.direct(webqtlConfig.GENODIR, _vals, _strains, fd.RISet, 8000)#XZ, 08/14/2008: add module name webqtlConfig
chrsInfo = d[2]
sum = 0
offsets = [0]
i = 0
for item in chrsInfo:
if i > 0:
offsets.append(sum)
sum += item[0]
i += 1
offsets.append(sum)
#print sum,offset,d[2]
canvasWidth = 880
canvasHeight = 880
if graphtype:
colorAreaWidth = 230
else:
colorAreaWidth = 0
c = pid.PILCanvas(size=(canvasWidth + colorAreaWidth ,canvasHeight))
xoffset = 40
yoffset = 40
width = canvasWidth - xoffset*2
height = canvasHeight - yoffset*2
xscale = width/sum
yscale = height/sum
rectInfo = d[1]
rectInfo.sort(webqtlUtil.cmpLRSFull)
finecolors = Plot.colorSpectrum(250)
finecolors.reverse()
regLRS = [0]*height
#draw LRS Full
for item in rectInfo:
LRSFull,LRSInteract,LRSa,LRSb,chras,chram,chrae,chrbs,chrbm,chrbe,chra,chrb,flanka,flankb = item
if LRSFull > 30:
dcolor = pid.red
elif LRSFull > 20:
dcolor = pid.orange
elif LRSFull > 10:
dcolor = pid.olivedrab
elif LRSFull > 0:
dcolor = pid.grey
else:
LRSFull = 0
dcolor = pid.grey
chras += offsets[chra]
chram += offsets[chra]
chrae += offsets[chra]
chrbs += offsets[chrb]
chrbm += offsets[chrb]
chrbe += offsets[chrb]
regLRSD = int(chram*yscale)
if regLRS[regLRSD] < LRSa:
regLRS[regLRSD] = LRSa
regLRSD = int(chrbm*yscale)
if regLRS[regLRSD] < LRSb:
regLRS[regLRSD] = LRSb
if graphtype:
colorIndex = int(LRSFull *250 /LRSFullThresh)
if colorIndex >= 250:
colorIndex = 249
dcolor = finecolors[colorIndex]
if chra != chrb or ((chrbe - chrae) > 10 and (chrbs - chras) > 10):
c.drawRect(xoffset+chrbs*xscale,yoffset+height-chras*yscale,xoffset+chrbe*xscale,yoffset+height-chrae*yscale,edgeColor=dcolor,fillColor=dcolor,edgeWidth = 0)
else:
c.drawPolygon([(xoffset+chrbs*xscale,yoffset+height-chras*yscale),(xoffset+chrbe*xscale,yoffset+height-chras*yscale),(xoffset+chrbe*xscale,yoffset+height-chrae*yscale)],edgeColor=dcolor,fillColor=dcolor,edgeWidth = 0,closed =1)
else:
c.drawCross(xoffset+chrbm*xscale,yoffset+height-chram*yscale,color=dcolor,size=2)
#draw Marker Regression LRS
if graphtype:
"""
maxLRS = max(regLRS)
pts = []
i = 0
for item in regLRS:
pts.append((xoffset+width+35+item*50/maxLRS, yoffset+height-i))
i += 1
c.drawPolygon(pts,edgeColor=pid.blue,edgeWidth=1,closed=0)
"""
LRS1Thresh = 16.2
i = 0
for item in regLRS:
colorIndex = int(item *250 /LRS1Thresh)
if colorIndex >= 250:
colorIndex = 249
dcolor = finecolors[colorIndex]
c.drawLine(xoffset+width+35,yoffset+height-i,xoffset+width+55,yoffset+height-i,color=dcolor)
i += 1
labelFont=pid.Font(ttf="arial",size=20,bold=0)
c.drawString('Single Locus Regression',xoffset+width+90,yoffset+height, font = labelFont,color=pid.dimgray,angle=90)
#draw LRS Interact
rectInfo.sort(webqtlUtil.cmpLRSInteract)
for item in rectInfo:
LRSFull,LRSInteract,LRSa,LRSb,chras,chram,chrae,chrbs,chrbm,chrbe,chra,chrb,flanka,flankb = item
if LRSInteract > 30:
dcolor = pid.red
elif LRSInteract > 20:
dcolor = pid.orange
elif LRSInteract > 10:
dcolor = pid.olivedrab
elif LRSInteract > 0:
dcolor = pid.grey
else:
LRSInteract = 0
dcolor = pid.grey
chras += offsets[chra]
chram += offsets[chra]
chrae += offsets[chra]
chrbs += offsets[chrb]
chrbm += offsets[chrb]
chrbe += offsets[chrb]
if graphtype:
colorIndex = int(LRSInteract *250 / LRSInteractThresh )
if colorIndex >= 250:
colorIndex = 249
dcolor = finecolors[colorIndex]
if chra != chrb or ((chrbe - chrae) > 10 and (chrbs - chras) > 10):
c.drawRect(xoffset+chras*xscale,yoffset+height-chrbs*yscale,xoffset+chrae*xscale,yoffset+height-chrbe*yscale,edgeColor=dcolor,fillColor=dcolor,edgeWidth = 0)
else:
c.drawPolygon([(xoffset+chras*xscale,yoffset+height-chrbs*yscale),(xoffset+chras*xscale,yoffset+height-chrbe*yscale),(xoffset+chrae*xscale,yoffset+height-chrbe*yscale)],edgeColor=dcolor,fillColor=dcolor,edgeWidth = 0,closed =1)
else:
c.drawCross(xoffset+chram*xscale,yoffset+height-chrbm*yscale,color=dcolor,size=2)
#draw chromosomes label
labelFont=pid.Font(ttf="tahoma",size=24,bold=0)
i = 0
for item in chrsInfo:
strWidth = c.stringWidth(item[1],font=labelFont)
c.drawString(item[1],xoffset+offsets[i]*xscale +(item[0]*xscale-strWidth)/2,canvasHeight -15,font = labelFont,color=pid.dimgray)
c.drawString(item[1],xoffset+offsets[i]*xscale +(item[0]*xscale-strWidth)/2,yoffset-10,font = labelFont,color=pid.dimgray)
c.drawString(item[1],xoffset-strWidth-5,yoffset+height - offsets[i]*yscale -(item[0]*yscale-22)/2,font = labelFont,color=pid.dimgray)
c.drawString(item[1],canvasWidth-xoffset+5,yoffset+height - offsets[i]*yscale -(item[0]*yscale-22)/2,font = labelFont,color=pid.dimgray)
i += 1
c.drawRect(xoffset,yoffset,xoffset+width,yoffset+height)
for item in offsets:
c.drawLine(xoffset,yoffset+height-item*yscale,xoffset+width,yoffset+height-item*yscale)
c.drawLine(xoffset+item*xscale,yoffset,xoffset+item*xscale,yoffset+height)
#draw pngMap
pngMap = HT.Map(name='pairPlotMap')
#print offsets, len(offsets)
for i in range(len(offsets)-1):
for j in range(len(offsets)-1):
COORDS = "%d,%d,%d,%d" %(xoffset+offsets[i]*xscale, yoffset+height-offsets[j+1]*yscale, xoffset+offsets[i+1]*xscale, yoffset+height-offsets[j]*yscale)
HREF = "javascript:showPairPlot(%d,%d);" % (i,j)
Areas = HT.Area(shape='rect',coords=COORDS,href=HREF)
pngMap.areas.append(Areas)
#draw spectrum
if graphtype:
i = 0
labelFont=pid.Font(ttf="tahoma",size=14,bold=0)
middleoffsetX = 180
for dcolor in finecolors:
if i % 50 == 0:
c.drawLine(xoffset+ width +middleoffsetX-15 , height + yoffset -i, xoffset+ width +middleoffsetX-20,height + yoffset -i, color=pid.black)
c.drawString('%d' % int(LRSInteractThresh*i/250.0),xoffset+ width+ middleoffsetX-40,height + yoffset -i +5, font = labelFont,color=pid.black)
c.drawLine(xoffset+ width +middleoffsetX+15 , height + yoffset -i, xoffset+ width +middleoffsetX+20 ,height + yoffset -i, color=pid.black)
c.drawString('%d' % int(LRSFullThresh*i/250.0),xoffset+ width + middleoffsetX+25,height + yoffset -i +5, font = labelFont,color=pid.black)
c.drawLine(xoffset+ width +middleoffsetX-15 , height + yoffset -i, xoffset+ width +middleoffsetX+15 ,height + yoffset -i, color=dcolor)
i += 1
if i % 50 == 0:
i -= 1
c.drawLine(xoffset+ width +middleoffsetX-15 , height + yoffset -i, xoffset+ width +middleoffsetX-20,height + yoffset -i, color=pid.black)
c.drawString('%d' % ceil(LRSInteractThresh*i/250.0),xoffset+ width + middleoffsetX-40,height + yoffset -i +5, font = labelFont,color=pid.black)
c.drawLine(xoffset+ width +middleoffsetX+15 , height + yoffset -i, xoffset+ width +middleoffsetX+20 ,height + yoffset -i, color=pid.black)
c.drawString('%d' % ceil(LRSFullThresh*i/250.0),xoffset+ width + middleoffsetX+25,height + yoffset -i +5, font = labelFont,color=pid.black)
labelFont=pid.Font(ttf="verdana",size=20,bold=0)
c.drawString('LRS Interaction',xoffset+ width + middleoffsetX-50,height + yoffset, font = labelFont,color=pid.dimgray,angle=90)
c.drawString('LRS Full',xoffset+ width + middleoffsetX+50,height + yoffset, font = labelFont,color=pid.dimgray,angle=90)
filename= webqtlUtil.genRandStr("Pair_")
c.save(webqtlConfig.IMGDIR+filename, format='png')
img2=HT.Image('/image/'+filename+'.png',border=0,usemap='#pairPlotMap')
form0 = HT.Form( cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), enctype='multipart/form-data', name='showPairPlot', submit=HT.Input(type='hidden'))
hddn0 = {'FormID':'pairPlot','Chr_A':'_','Chr_B':'','idata':string.join(map(str, _vals), ','),'istrain':string.join(_strains, ','),'RISet':fd.RISet}
for key in hddn0.keys():
form0.append(HT.Input(name=key, value=hddn0[key], type='hidden'))
form0.append(img2, pngMap)
mainfmName = webqtlUtil.genRandStr("fm_")
txtform = HT.Form( cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), enctype='multipart/form-data', name=mainfmName, submit=HT.Input(type='hidden'))
hddn = {'FormID':'showDatabase','ProbeSetID':'_','database':fd.RISet+"Geno",'CellID':'_','RISet':fd.RISet}
#XZ, Aug 11, 2010: The variable traitStrains is not assigned right values before (should not be assigned fd.strainlist).
#hddn['traitStrains'] = string.join(fd.strainlist, ',')
hddn['traitStrains'] = string.join(_strains, ',')
hddn['traitValues'] = string.join(map(str, _vals), ',')
hddn['interval1'] = ''
hddn['interval2'] = ''
if fd.incparentsf1:
hddn['incparentsf1']='ON'
for key in hddn.keys():
txtform.append(HT.Input(name=key, value=hddn[key], type='hidden'))
tbl = HT.TableLite(Class="collap", cellspacing=1, cellpadding=5,width=canvasWidth + colorAreaWidth)
c1 = HT.TD('Interval 1',colspan=3,align="Center", Class="fs13 fwb ffl b1 cw cbrb")
c2 = HT.TD('Interval 2',colspan=3,align="Center", Class="fs13 fwb ffl b1 cw cbrb")
c11 = HT.TD('Position',rowspan=2,align="Center", Class="fs13 fwb ffl b1 cw cbrb")
c12 = HT.TD('Flanking Markers',colspan=2,align="Center", Class="fs13 fwb ffl b1 cw cbrb")
c111 = HT.TD('Proximal',align="Center", Class="fs13 fwb ffl b1 cw cbrb")
c112 = HT.TD('Distal',align="Center", Class="fs13 fwb ffl b1 cw cbrb")
c3 = HT.TD('LRS Full',rowspan=3,align="Center", Class="fs13 fwb ffl b1 cw cbrb")
c4 = HT.TD('LRS Additive',rowspan=3,align="Center", Class="fs13 fwb ffl b1 cw cbrb")
c5 = HT.TD('LRS Interact',rowspan=3,align="Center", Class="fs13 fwb ffl b1 cw cbrb")
c6 = HT.TD('LRS 1',rowspan=3,align="Center", Class="fs13 fwb ffl b1 cw cbrb")
c7 = HT.TD('LRS 2',rowspan=3,align="Center", Class="fs13 fwb ffl b1 cw cbrb")
tbl.append(HT.TR(c1,c3,c4,c5,c6,c7,c2))
tbl.append(HT.TR(c11,c12,c11,c12))
tbl.append(HT.TR(c111,c112,c111,c112))
if not graphsort: #Sort by LRS Full
rectInfo.sort(webqtlUtil.cmpLRSFull)
rectInfoReturned = rectInfo[len(rectInfo) - returnIntervalPairNum:]
rectInfoReturned.reverse()
for item in rectInfoReturned:
LRSFull,LRSInteract,LRSa,LRSb,chras,chram,chrae,chrbs,chrbm,chrbe,chra,chrb,flanka,flankb = item
LRSAdditive = LRSFull - LRSInteract
flanka1,flanka2 = string.split(flanka)
flankb1,flankb2 = string.split(flankb)
urla1 = HT.Href(text = flanka1, url = "javascript:showTrait('%s','%s');" % (mainfmName, flanka1),Class= "fs12 fwn")
urla2 = HT.Href(text = flanka2, url = "javascript:showTrait('%s','%s');" % (mainfmName, flanka2),Class= "fs12 fwn")
urlb1 = HT.Href(text = flankb1, url = "javascript:showTrait('%s','%s');" % (mainfmName, flankb1),Class= "fs12 fwn")
urlb2 = HT.Href(text = flankb2, url = "javascript:showTrait('%s','%s');" % (mainfmName, flankb2),Class= "fs12 fwn")
urlGenGraph = HT.Href(text = "Plot", url = "javascript:showCateGraph('%s', '%s %s %2.3f', '%s %s %2.3f');" % (mainfmName, flanka1, flanka2, chram, flankb1, flankb2, chrbm),Class= "fs12 fwn")
tr1 = HT.TR(
HT.TD('Chr %s @ %2.1f cM ' % (chrsInfo[chra][1],chram),Class= "fs12 b1 fwn"),
HT.TD(urla1,Class= "fs12 b1 fwn"),
HT.TD(urla2,Class= "fs12 b1 fwn"),
HT.TD('%2.3f ' % LRSFull, urlGenGraph,Class= "fs12 b1 fwn"),
HT.TD('%2.3f' % LRSAdditive,Class= "fs12 b1 fwn"),
HT.TD('%2.3f' % LRSInteract,Class= "fs12 b1 fwn"),
HT.TD('%2.3f' % LRSa,Class= "fs12 b1 fwn"),
HT.TD('%2.3f' % LRSb,Class= "fs12 b1 fwn"),
HT.TD('Chr %s @ %2.1f cM' % (chrsInfo[chrb][1],chrbm),Class= "fs12 b1 fwn"),
HT.TD(urlb1,Class= "fs12 b1 fwn"),
HT.TD(urlb2,Class= "fs12 b1 fwn"))
tbl.append(tr1)
plotType1 = HT.Input(type="radio", name="plotType", value ="Dot", checked=1)
plotType2 = HT.Input(type="radio", name="plotType", value ="Box")
plotText = HT.Paragraph("Plot Type : ", plotType1, " Dot ", plotType2, " Box", )
txtform.append(plotText, tbl)
TD_LR = HT.TD(colspan=2,height=200,width="100%",bgColor='#eeeeee')
TD_LR.append(main_title,HT.Blockquote(subtitle1, pairIntro, HT.P(), HT.Center(form0,HT.P())),HT.Blockquote(subtitle2, permuIntro,HT.P(), HT.Center(permuTbl)), HT.Blockquote(subtitle3, tblIntro, HT.P(),HT.Center(txtform), HT.P()))
self.dict['body'] = str(TD_LR)
else:
heading = "Direct Plot"
detail = ['Fewer than %d strain data were entered for %s data set. No statitical analysis has been attempted.' % (webqtlConfig.KMININFORMATIVE, fd.RISet)]
self.error(heading=heading,detail=detail)
return
else:
heading = "Direct Plot"
detail = ['Empty data set, please check your data.']
self.error(heading=heading,detail=detail)
return
def __init__(self, fd):
templatePage.__init__(self, fd)
self.initializeDisplayParameters(fd)
if not fd.genotype:
fd.readGenotype()
if fd.allstrainlist:
mdpchoice = fd.formdata.getvalue('MDPChoice')
if mdpchoice == "1":
strainlist = fd.f1list + fd.strainlist
elif mdpchoice == "2":
strainlist = []
strainlist2 = fd.f1list + fd.strainlist
for strain in fd.allstrainlist:
if strain not in strainlist2:
strainlist.append(strain)
#So called MDP Panel
if strainlist:
strainlist = fd.f1list+fd.parlist+strainlist
else:
strainlist = fd.allstrainlist
fd.readData(fd.allstrainlist)
else:
mdpchoice = None
strainlist = fd.strainlist
fd.readData()
#if fd.allstrainlist:
# fd.readData(fd.allstrainlist)
# strainlist = fd.allstrainlist
#else:
# fd.readData()
# strainlist = fd.strainlist
if not self.openMysql():
return
isSampleCorr = 0 #XZ: initial value is false
isTissueCorr = 0 #XZ: initial value is false
#Javascript functions (showCorrelationPlot2, showTissueCorrPlot) have made sure the correlation type is either sample correlation or tissue correlation.
if (self.database and (self.ProbeSetID != 'none')):
isSampleCorr = 1
elif (self.X_geneSymbol and self.Y_geneSymbol):
isTissueCorr = 1
else:
heading = "Correlation Type Error"
detail = ["For the input parameters, GN can not recognize the correlation type is sample correlation or tissue correlation."]
self.error(heading=heading,detail=detail)
return
TD_LR = HT.TD(colspan=2,height=200,width="100%",bgColor='#eeeeee', align="left", wrap="off")
dataX=[]
dataY=[]
dataZ=[] # shortname
fullTissueName=[]
if isTissueCorr:
dataX, dataY, xlabel, ylabel, dataZ, fullTissueName = self.getTissueLabelsValues(X_geneSymbol=self.X_geneSymbol, Y_geneSymbol=self.Y_geneSymbol, TissueProbeSetFreezeId=self.TissueProbeSetFreezeId)
plotHeading = HT.Paragraph('Tissue Correlation Scatterplot')
plotHeading.__setattr__("class","title")
if self.xAxisLabel == '':
self.xAxisLabel = xlabel
if self.yAxisLabel == '':
self.yAxisLabel = ylabel
if isSampleCorr:
plotHeading = HT.Paragraph('Sample Correlation Scatterplot')
plotHeading.__setattr__("class","title")
#XZ: retrieve trait 1 info, Y axis
trait1_data = [] #trait 1 data
trait1Url = ''
try:
Trait1 = webqtlTrait(db=self.database, name=self.ProbeSetID, cellid=self.CellID, cursor=self.cursor)
Trait1.retrieveInfo()
Trait1.retrieveData()
except:
heading = "Retrieve Data"
detail = ["The database you just requested has not been established yet."]
self.error(heading=heading,detail=detail)
return
trait1_data = Trait1.exportData(strainlist)
if Trait1.db.type == 'Publish' and Trait1.confidential:
trait1Url = Trait1.genHTML(dispFromDatabase=1, privilege=self.privilege, userName=self.userName, authorized_users=Trait1.authorized_users)
else:
trait1Url = Trait1.genHTML(dispFromDatabase=1)
if self.yAxisLabel == '':
self.yAxisLabel= '%s : %s' % (Trait1.db.shortname, Trait1.name)
if Trait1.cellid:
self.yAxisLabel += ' : ' + Trait1.cellid
#XZ, retrieve trait 2 info, X axis
traitdata2 = [] #trait 2 data
_vals = [] #trait 2 data
trait2Url = ''
if ( self.database2 and (self.ProbeSetID2 != 'none') ):
try:
Trait2 = webqtlTrait(db=self.database2, name=self.ProbeSetID2, cellid=self.CellID2, cursor=self.cursor)
Trait2.retrieveInfo()
Trait2.retrieveData()
except:
heading = "Retrieve Data"
detail = ["The database you just requested has not been established yet."]
self.error(heading=heading,detail=detail)
return
if Trait2.db.type == 'Publish' and Trait2.confidential:
trait2Url = Trait2.genHTML(dispFromDatabase=1, privilege=self.privilege, userName=self.userName, authorized_users=Trait2.authorized_users)
else:
trait2Url = Trait2.genHTML(dispFromDatabase=1)
traitdata2 = Trait2.exportData(strainlist)
_vals = traitdata2[:]
if self.xAxisLabel == '':
self.xAxisLabel = '%s : %s' % (Trait2.db.shortname, Trait2.name)
if Trait2.cellid:
self.xAxisLabel += ' : ' + Trait2.cellid
else:
for item in strainlist:
if fd.allTraitData.has_key(item):
_vals.append(fd.allTraitData[item].val)
else:
_vals.append(None)
if self.xAxisLabel == '':
if fd.identification:
self.xAxisLabel = fd.identification
else:
self.xAxisLabel = "User Input Data"
try:
Trait2 = webqtlTrait(fullname=fd.formdata.getvalue('fullname'), cursor=self.cursor)
trait2Url = Trait2.genHTML(dispFromDatabase=1)
except:
trait2Url = self.xAxisLabel
if (_vals and trait1_data):
if len(_vals) != len(trait1_data):
errors = HT.Blockquote(HT.Font('Error: ',color='red'),HT.Font('The number of traits are inconsistent, Program quit',color='black'))
errors.__setattr__("class","subtitle")
TD_LR.append(errors)
self.dict['body'] = str(TD_LR)
return
for i in range(len(_vals)):
if _vals[i]!= None and trait1_data[i]!= None:
dataX.append(_vals[i])
dataY.append(trait1_data[i])
strainName = strainlist[i]
if self.showstrains:
dataZ.append(webqtlUtil.genShortStrainName(RISet=fd.RISet, input_strainName=strainName))
else:
heading = "Correlation Plot"
detail = ['Empty Dataset for sample correlation, please check your data.']
self.error(heading=heading,detail=detail)
return
#XZ: We have gotten all data for both traits.
if len(dataX) >= self.corrMinInformative:
if self.rankOrder == 0:
rankPrimary = 0
rankSecondary = 1
else:
rankPrimary = 1
rankSecondary = 0
lineColor = self.setLineColor();
symbolColor = self.setSymbolColor();
idColor = self.setIdColor();
c = pid.PILCanvas(size=(self.plotSize, self.plotSize*0.90))
data_coordinate = Plot.plotXY(canvas=c, dataX=dataX, dataY=dataY, rank=rankPrimary, dataLabel = dataZ, labelColor=pid.black, lineSize=self.lineSize, lineColor=lineColor, idColor=idColor, idFont=self.idFont, idSize=self.idSize, symbolColor=symbolColor, symbolType=self.symbol, filled=self.filled, symbolSize=self.symbolSize, XLabel=self.xAxisLabel, connectdot=0, YLabel=self.yAxisLabel, title='', fitcurve=self.showline, displayR =1, offset= (90, self.plotSize/20, self.plotSize/10, 90), showLabel = self.showIdentifiers)
if rankPrimary == 1:
dataXlabel, dataYlabel = webqtlUtil.calRank(xVals=dataX, yVals=dataY, N=len(dataX))
else:
dataXlabel, dataYlabel = dataX, dataY
gifmap1 = HT.Map(name='CorrelationPlotImageMap1')
for i, item in enumerate(data_coordinate):
one_rect_coordinate = "%d, %d, %d, %d" % (item[0] - 5, item[1] - 5, item[0] + 5, item[1] + 5)
if isTissueCorr:
one_rect_title = "%s (%s, %s)" % (fullTissueName[i], dataXlabel[i], dataYlabel[i])
else:
one_rect_title = "%s (%s, %s)" % (dataZ[i], dataXlabel[i], dataYlabel[i])
gifmap1.areas.append(HT.Area(shape='rect',coords=one_rect_coordinate, title=one_rect_title) )
filename= webqtlUtil.genRandStr("XY_")
c.save(webqtlConfig.IMGDIR+filename, format='gif')
img1=HT.Image('/image/'+filename+'.gif',border=0, usemap='#CorrelationPlotImageMap1')
mainForm_1 = 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':'_','RISet':fd.RISet, 'ProbeSetID2':'_', 'database2':'_', 'CellID2':'_', 'allstrainlist':string.join(fd.strainlist, " "), 'traitList': fd.formdata.getvalue("traitList")}
if fd.incparentsf1:
hddn['incparentsf1'] = 'ON'
for key in hddn.keys():
mainForm_1.append(HT.Input(name=key, value=hddn[key], type='hidden'))
if isSampleCorr:
mainForm_1.append(HT.P(), HT.Blockquote(HT.Strong('X axis:'),HT.Blockquote(trait2Url),HT.Strong('Y axis:'),HT.Blockquote(trait1Url), style='width: %spx;' % self.plotSize, wrap="hard"))
graphForm = HT.Form(cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), name='MDP_Form',submit=HT.Input(type='hidden'))
graph_hddn = self.setHiddenParameters(fd, rankPrimary)
webqtlUtil.exportData(graph_hddn, fd.allTraitData) #XZ: This is necessary to replot with different groups of strains
for key in graph_hddn.keys():
graphForm.append(HT.Input(name=key, value=graph_hddn[key], type='hidden'))
options = self.createOptionsMenu(fd, mdpchoice)
if (self.showOptions == '0'):
showOptionsButton = HT.Input(type='button' ,name='optionsButton',value='Hide Options', onClick="showHideOptions();", Class="button")
else:
showOptionsButton = HT.Input(type='button' ,name='optionsButton',value='Show Options', onClick="showHideOptions();", Class="button")
# updated by NL: 12-07-2011 add variables for tissue abbreviation page
if isTissueCorr:
graphForm.append(HT.Input(name='shortTissueName', value='', type='hidden'))
graphForm.append(HT.Input(name='fullTissueName', value='', type='hidden'))
shortTissueNameStr=string.join(dataZ, ",")
fullTissueNameStr=string.join(fullTissueName, ",")
tissueAbbrButton=HT.Input(type='button' ,name='tissueAbbrButton',value='Show Abbreviations', onClick="showTissueAbbr('MDP_Form','%s','%s')" % (shortTissueNameStr,fullTissueNameStr), Class="button")
graphForm.append(showOptionsButton,' ',tissueAbbrButton, HT.BR(), HT.BR())
else:
graphForm.append(showOptionsButton, HT.BR(), HT.BR())
graphForm.append(options, HT.BR())
graphForm.append(HT.HR(), HT.BR(), HT.P())
TD_LR.append(plotHeading, HT.BR(),graphForm, HT.BR(), gifmap1, HT.P(), img1, HT.P(), mainForm_1)
TD_LR.append(HT.BR(), HT.HR(color="grey", size=5, width="100%"))
c = pid.PILCanvas(size=(self.plotSize, self.plotSize*0.90))
data_coordinate = Plot.plotXY(canvas=c, dataX=dataX, dataY=dataY, rank=rankSecondary, dataLabel = dataZ, labelColor=pid.black,lineColor=lineColor, lineSize=self.lineSize, idColor=idColor, idFont=self.idFont, idSize=self.idSize, symbolColor=symbolColor, symbolType=self.symbol, filled=self.filled, symbolSize=self.symbolSize, XLabel=self.xAxisLabel, connectdot=0, YLabel=self.yAxisLabel,title='', fitcurve=self.showline, displayR =1, offset= (90, self.plotSize/20, self.plotSize/10, 90), showLabel = self.showIdentifiers)
if rankSecondary == 1:
dataXlabel, dataYlabel = webqtlUtil.calRank(xVals=dataX, yVals=dataY, N=len(dataX))
else:
dataXlabel, dataYlabel = dataX, dataY
gifmap2 = HT.Map(name='CorrelationPlotImageMap2')
for i, item in enumerate(data_coordinate):
one_rect_coordinate = "%d, %d, %d, %d" % (item[0] - 6, item[1] - 6, item[0] + 6, item[1] + 6)
if isTissueCorr:
one_rect_title = "%s (%s, %s)" % (fullTissueName[i], dataXlabel[i], dataYlabel[i])
else:
one_rect_title = "%s (%s, %s)" % (dataZ[i], dataXlabel[i], dataYlabel[i])
gifmap2.areas.append(HT.Area(shape='rect',coords=one_rect_coordinate, title=one_rect_title) )
filename= webqtlUtil.genRandStr("XY_")
c.save(webqtlConfig.IMGDIR+filename, format='gif')
img2=HT.Image('/image/'+filename+'.gif',border=0, usemap='#CorrelationPlotImageMap2')
mainForm_2 = HT.Form( cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), enctype='multipart/form-data', name='showDatabase2', submit=HT.Input(type='hidden'))
hddn = {'FormID':'showDatabase2','ProbeSetID':'_','database':'_','CellID':'_','RISet':fd.RISet, 'ProbeSetID2':'_', 'database2':'_', 'CellID2':'_', 'allstrainlist':string.join(fd.strainlist, " "), 'traitList': fd.formdata.getvalue("traitList")}
if fd.incparentsf1:
hddn['incparentsf1'] = 'ON'
for key in hddn.keys():
mainForm_2.append(HT.Input(name=key, value=hddn[key], type='hidden'))
if isSampleCorr:
mainForm_2.append(HT.P(), HT.Blockquote(HT.Strong('X axis:'),HT.Blockquote(trait2Url),HT.Strong('Y axis:'),HT.Blockquote(trait1Url), style='width:%spx;' % self.plotSize))
TD_LR.append(HT.BR(), HT.P())
TD_LR.append('\n', gifmap2, HT.P(), HT.P(), img2, HT.P(), mainForm_2)
self.dict['body'] = str(TD_LR)
else:
heading = "Correlation Plot"
detail = ['Fewer than %d strain data were entered for %s data set. No statitical analysis has been attempted.' % (self.corrMinInformative, fd.RISet)]
self.error(heading=heading,detail=detail)
return
def GenReport(self, fd, _genotype, _strains, _vals, _vars= []):
'Create an HTML division which reports any loci which are significantly associated with the submitted trait data.'
if webqtlUtil.ListNotNull(_vars):
qtlresults = _genotype.regression(strains = _strains, trait = _vals, variance = _vars, control = self.controlLocus)
LRSArray = _genotype.permutation(strains = _strains, trait = _vals, variance = _vars, nperm=fd.nperm)
else:
qtlresults = _genotype.regression(strains = _strains, trait = _vals, control = self.controlLocus)
LRSArray = _genotype.permutation(strains = _strains, trait = _vals,nperm=fd.nperm)
myCanvas = pid.PILCanvas(size=(400,300))
#plotBar(myCanvas,10,10,390,290,LRSArray,XLabel='LRS',YLabel='Frequency',title=' Histogram of Permutation Test',identification=fd.identification)
Plot.plotBar(myCanvas, LRSArray,XLabel='LRS',YLabel='Frequency',title=' Histogram of Permutation Test')
filename= webqtlUtil.genRandStr("Reg_")
myCanvas.save(webqtlConfig.IMGDIR+filename, format='gif')
img=HT.Image('/image/'+filename+'.gif',border=0,alt='Histogram of Permutation Test')
if fd.suggestive == None:
fd.suggestive = LRSArray[int(fd.nperm*0.37-1)]
else:
fd.suggestive = float(fd.suggestive)
if fd.significance == None:
fd.significance = LRSArray[int(fd.nperm*0.95-1)]
else:
fd.significance = float(fd.significance)
#########################################
# Permutation Graph
#########################################
permutationHeading = HT.Paragraph('Histogram of Permutation Test')
permutationHeading.__setattr__("class","title")
lrs = HT.Blockquote('Total of %d permutations' % fd.nperm,HT.P(),'Suggestive LRS = %2.2f' % LRSArray[int(fd.nperm*0.37-1)],\
HT.BR(),'Significant LRS = %2.2f' % LRSArray[int(fd.nperm*0.95-1)],HT.BR(),'Highly Significant LRS =%2.2f' % LRSArray[int(fd.nperm*0.99-1)])
permutation = HT.TableLite()
permutation.append(HT.TR(HT.TD(img)),HT.TR(HT.TD(lrs)))
_dispAllLRS = 0
if fd.formdata.getvalue('displayAllLRS'):
_dispAllLRS = 1
qtlresults2 = []
if _dispAllLRS:
filtered = qtlresults[:]
else:
filtered = filter(lambda x, y=fd.suggestive: x.lrs > y, qtlresults)
if len(filtered) == 0:
qtlresults2 = qtlresults[:]
qtlresults2.sort()
filtered = qtlresults2[-10:]
#########################################
# Marker regression report
#########################################
locusFormName = webqtlUtil.genRandStr("fm_")
locusForm = HT.Form(cgi = os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), \
enctype='multipart/form-data', name=locusFormName, submit=HT.Input(type='hidden'))
hddn = {'FormID':'showDatabase','ProbeSetID':'_','database':fd.RISet+"Geno",'CellID':'_', \
'RISet':fd.RISet, 'incparentsf1':'on'}
for key in hddn.keys():
locusForm.append(HT.Input(name=key, value=hddn[key], type='hidden'))
regressionHeading = HT.Paragraph('Marker Regression Report')
regressionHeading.__setattr__("class","title")
if qtlresults2 != []:
report = HT.Blockquote(HT.Font('No association ',color="#FF0000"),HT.Font('with a likelihood ratio statistic greater than %3.1f was found. Here are the top 10 LRSs.' % fd.suggestive,color="#000000"))
else:
report = HT.Blockquote('The following loci in the %s data set have associations with the above trait data.\n' % fd.RISet, HT.P())
report.__setattr__("class","normalsize")
fpText = open('%s.txt' % (webqtlConfig.TMPDIR+filename), 'wb')
textUrl = HT.Href(text = 'Download', url= '/tmp/'+filename+'.txt', target = "_blank", Class='fs12 fwn')
bottomInfo = HT.Paragraph(textUrl, ' result in tab-delimited text format.', HT.BR(), HT.BR(),'LRS values marked with',HT.Font(' * ',color="red"), 'are greater than the significance threshold (specified by you or by permutation test). ' , HT.BR(), HT.BR(), HT.Strong('Additive Effect'), ' is half the difference in the mean phenotype of all cases that are homozygous for one parental allel at this marker minus the mean of all cases that are homozygous for the other parental allele at this marker. ','In the case of %s strains, for example,' % fd.RISet,' A positive additive effect indicates that %s alleles increase trait values. Negative additive effect indicates that %s alleles increase trait values.'% (fd.ppolar,fd.mpolar),Class="fs12 fwn")
c1 = HT.TD('LRS',Class="fs14 fwb ffl b1 cw cbrb")
c2 = HT.TD('Chr',Class="fs14 fwb ffl b1 cw cbrb")
c3 = HT.TD('Mb',Class="fs14 fwb ffl b1 cw cbrb")
c4 = HT.TD('Locus',Class="fs14 fwb ffl b1 cw cbrb")
c5 = HT.TD('Additive Effect',Class="fs14 fwb ffl b1 cw cbrb")
fpText.write('LRS\tChr\tMb\tLocus\tAdditive Effect\n')
hr = HT.TR(c1, c2, c3, c4, c5)
tbl = HT.TableLite(border=0, width="90%", cellpadding=0, cellspacing=0, Class="collap")
tbl.append(hr)
for ii in filtered:
#add by NL 06-22-2011: set LRS to 460 when LRS is infinite,
if ii.lrs==float('inf') or ii.lrs>webqtlConfig.MAXLRS:
LRS=webqtlConfig.MAXLRS #maximum LRS value
else:
LRS=ii.lrs
fpText.write('%2.3f\t%s\t%s\t%s\t%2.3f\n' % (LRS, ii.locus.chr, ii.locus.Mb, ii.locus.name, ii.additive))
if LRS > fd.significance:
c1 = HT.TD('%3.3f*' % LRS, Class="fs13 b1 cbw cr")
else:
c1 = HT.TD('%3.3f' % LRS,Class="fs13 b1 cbw c222")
tbl.append(HT.TR(c1, HT.TD(ii.locus.chr,Class="fs13 b1 cbw c222"), HT.TD(ii.locus.Mb,Class="fs13 b1 cbw c222"), HT.TD(HT.Href(text=ii.locus.name, url = "javascript:showTrait('%s','%s');" % (locusFormName, ii.locus.name), Class='normalsize'), Class="fs13 b1 cbw c222"), HT.TD('%3.3f' % ii.additive,Class="fs13 b1 cbw c222"),bgColor='#eeeeee'))
locusForm.append(tbl)
tbl2 = HT.TableLite(border=0, cellspacing=0, cellpadding=0,width="90%")
tbl2.append(HT.TR(HT.TD(bottomInfo)))
rv=HT.TD(permutationHeading,HT.Center(permutation),regressionHeading,report, HT.Center(locusForm,HT.P(),tbl2,HT.P()),width='55%',valign='top', bgColor='#eeeeee')
return rv
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 insertUpdateCheck(self, fd, warning= ""):
self.dict['title'] = "%s GeneWiki Entry for %s" % (self.action.title(), self.symbol)
#mailsrch = re.compile('([\w\-][\w\-\.]*@[\w\-][\w\-\.]+[a-zA-Z]{1,4})([\s,;])*')
mailsrch = re.compile('([\w\-][\w\-\.]*)@([\w\-\.]+)\.([a-zA-Z]{1,4})([\s,;])*')
httpsrch = re.compile('((?:http|ftp|gopher|file)://(?:[^ \n\r<\)]+))([\s,;])*')
if not self.comment or not self.email:
heading = self.dict['title']
detail = ["Please don't leave text field or email field empty."]
self.error(heading=heading,detail=detail,error="Error")
return
if self.action == 'update' and not self.reason:
heading = self.dict['title']
detail = ["Please submit your reason for this modification."]
self.error(heading=heading,detail=detail,error="Error")
return
if len(self.comment) >500:
heading = self.dict['title']
detail = ["Your entry is more than 500 characters."]
self.error(heading=heading,detail=detail,error="Error")
return
if self.email and re.sub(mailsrch, "", self.email) != "":
heading = self.dict['title']
detail = ["The format of your email address is incorrect."]
self.error(heading=heading,detail=detail,error="Error")
return
if self.weburl == "http://":
self.weburl = ""
if self.weburl and re.sub(httpsrch, "", self.weburl) != "":
heading = self.dict['title']
detail = ["The format of web resource link is incorrect."]
self.error(heading=heading,detail=detail,error="Error")
return
if self.pubmedid:
try:
test = map(int, string.split(self.pubmedid))
except:
heading = self.dict['title']
detail = ["PubMed IDs can only be integers."]
self.error(heading=heading,detail=detail,error="Error")
return
form = HT.Form(cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), name='addgenerif',submit=HT.Input(type='hidden'))
recordInfoTable = HT.TableLite(border=0, cellspacing=1, cellpadding=5,align="center")
addButton = HT.Input(type='submit',name='submit', value='%s GeneWiki Entry' % self.action.title(),Class="button")
hddn = {'curStatus':'insertResult', 'FormID':'geneWiki', 'symbol':self.symbol,
'comment':self.comment, 'email':self.email, 'species':self.species,
'action':self.action, 'reason':self.reason}
if self.Id:
hddn['Id']=self.Id
formBody = HT.TableLite()
formBody.append(HT.TR(
HT.TD(HT.Strong("Species: ")),
HT.TD(width=10),
HT.TD(string.split(self.species, ":")[0])
))
if self.pubmedid:
try:
formBody.append(HT.TR(
HT.TD(HT.Strong("PubMed IDs: ")),
HT.TD(width=10),
HT.TD(self.pubmedid)
))
hddn['pubmedid'] = self.pubmedid
except:
pass
if self.weburl:
try:
formBody.append(HT.TR(
HT.TD(HT.Strong("Web URL: ")),
HT.TD(width=10),
HT.TD(HT.Href(text=self.weburl, url=self.weburl, Class='fwn'))
))
hddn['weburl'] = self.weburl
except:
pass
formBody.append(HT.TR(
HT.TD(HT.Strong("Gene Notes: ")),
HT.TD(width=10),
HT.TD(self.comment)
))
formBody.append(HT.TR(
HT.TD(HT.Strong("Email: ")),
HT.TD(width=10),
HT.TD(self.email)
))
if self.initial:
formBody.append(HT.TR(
HT.TD(HT.Strong("Initial: ")),
HT.TD(width=10),
HT.TD(self.initial)
))
hddn['initial'] = self.initial
if self.genecategory:
cTD = HT.TD()
if type(self.genecategory) == type(""):
self.genecategory = string.split(self.genecategory)
self.cursor.execute("Select Id, Name from GeneCategory where Id in (%s) order by Name " % string.join(self.genecategory, ', '))
results = self.cursor.fetchall()
for item in results:
cTD.append(item[1], HT.BR())
formBody.append(HT.TR(
HT.TD(HT.Strong("Category: ")),
HT.TD(width=10),
cTD
))
hddn['genecategory'] = string.join(self.genecategory, " ")
formBody.append(HT.TR(
HT.TD(
HT.BR(), HT.BR(),
HT.Div("For security reasons, enter the code (case insensitive) in the image below to finalize your submission"), HT.BR(),
addButton, HT.Input(type="password", size = 25, name="password"),
colspan=3)
))
code = webqtlUtil.genRandStr(length=5, chars="abcdefghkmnpqrstuvwxyzABCDEFGHJKMNPQRSTUVWXYZ23456789")
filename= webqtlUtil.genRandStr("Sec_")
hddn['filename'] = filename
securityCanvas = pid.PILCanvas(size=(300,100))
Plot.plotSecurity(securityCanvas, text=code)
os.system("touch %s_.%s" % (os.path.join(webqtlConfig.IMGDIR,filename), code))
securityCanvas.save(os.path.join(webqtlConfig.IMGDIR,filename), format='png')
formBody.append(HT.TR(
HT.TD(HT.Image("/image/"+filename+".png"), colspan=3)
))
hddn['filename'] = filename
TD_LR = HT.TD(valign="top", bgcolor="#eeeeee")
title = HT.Paragraph("%s GeneWiki Entry for %s" % (self.action.title(), self.symbol), Class="title")
form.append(HT.P(), HT.Blockquote(formBody))
for key in hddn.keys():
form.append(HT.Input(name=key, value=hddn[key], type='hidden'))
TD_LR.append(title, HT.Blockquote(warning, Id="red"), form)
self.dict['body'] = TD_LR
def __init__(self, fd):
LRSFullThresh = 30
LRSInteractThresh = 25
maxPlotSize = 1000
mainfmName = webqtlUtil.genRandStr("fm_")
templatePage.__init__(self, fd)
self.dict['title'] = 'Pair-Scan Plot'
if not self.openMysql():
return
TD_LR = HT.TD(height=200,width="100%",bgColor='#eeeeee')
vals = fd.formdata.getvalue('idata')
vals = map(float,string.split(vals,','))
strains = fd.formdata.getvalue('istrain')
strains = string.split(strains,',')
Chr_A = int(fd.formdata.getvalue('Chr_A'))
Chr_B = int(fd.formdata.getvalue('Chr_B'))
if len(vals) > webqtlConfig.KMININFORMATIVE:
d = direct.exhaust(webqtlConfig.GENODIR, vals, strains, fd.RISet, Chr_A, Chr_B)#XZ, 08/14/2008: add module name webqtlConfig
chrsInfo = d[2]
longerChrLen = max(chrsInfo[Chr_A][0], chrsInfo[Chr_B][0])
shorterChrlen = min(chrsInfo[Chr_A][0], chrsInfo[Chr_B][0])
plotHeight = int(chrsInfo[Chr_B][0]*maxPlotSize/longerChrLen)
plotWidth = int(chrsInfo[Chr_A][0]*maxPlotSize/longerChrLen)
xLeftOffset = 200
xRightOffset = 40
yTopOffset = 40
yBottomOffset = 200
colorAreaWidth = 120
canvasHeight = plotHeight + yTopOffset + yBottomOffset
canvasWidth = plotWidth + xLeftOffset + xRightOffset + colorAreaWidth
canvas = pid.PILCanvas(size=(canvasWidth,canvasHeight))
plotScale = plotHeight/chrsInfo[Chr_B][0]
rectInfo = d[1]
finecolors = Plot.colorSpectrum(250)
finecolors.reverse()
#draw LRS Full
for item in rectInfo:
LRSFull,LRSInteract,LRSa,LRSb,chras,chram,chrae,chrbs,chrbm,chrbe,chra,chrb,flanka,flankb = item
if Chr_A > Chr_B:
colorIndex = int(LRSFull *250 /LRSFullThresh)
else:
colorIndex = int(LRSInteract *250 /LRSInteractThresh)
if colorIndex >= 250:
colorIndex = 249
elif colorIndex < 0:
colorIndex = 0
dcolor = finecolors[colorIndex]
if chra != chrb or (abs(chrbe - chrae) > 10 and abs(chrbs - chras) > 10):
canvas.drawRect(xLeftOffset+chras*plotScale,yTopOffset+plotHeight- \
chrbs*plotScale,xLeftOffset+chrae*plotScale,yTopOffset+plotHeight- \
chrbe*plotScale,edgeColor=dcolor,fillColor=dcolor,edgeWidth = 0)
elif chrbs >= chras:
canvas.drawPolygon([(xLeftOffset+chras*plotScale,yTopOffset+plotHeight-chrbs*plotScale),\
(xLeftOffset+chras*plotScale,yTopOffset+plotHeight-chrbe*plotScale),\
(xLeftOffset+chrae*plotScale,yTopOffset+plotHeight-chrbe*plotScale)],\
edgeColor=dcolor,fillColor=dcolor,edgeWidth = 0,closed =1)
else:
canvas.drawPolygon([(xLeftOffset+chras*plotScale,yTopOffset+plotHeight-chrbs*plotScale),\
(xLeftOffset+chrae*plotScale,yTopOffset+plotHeight-chrbs*plotScale), \
(xLeftOffset+chrae*plotScale,yTopOffset+plotHeight-chrbe*plotScale)], \
edgeColor=dcolor,fillColor=dcolor,edgeWidth = 0,closed =1)
labelFont=pid.Font(ttf="verdana",size=24,bold=0)
chrName = "chromosome %s" % chrsInfo[Chr_A][1]
canvas.drawString(chrName,xLeftOffset + (plotWidth - canvas.stringWidth(chrName,font=labelFont))/2,\
yTopOffset+plotHeight+ 170,font=labelFont)
chrName = "chromosome %s" % chrsInfo[Chr_B][1]
canvas.drawString(chrName, 30, yTopOffset +(canvas.stringWidth(chrName,font=labelFont) + plotHeight)/2,\
font=labelFont, angle = 90)
if Chr_A == Chr_B:
infoStr = "minimum distance = 10 cM"
infoStrWidth = canvas.stringWidth(infoStr,font=labelFont)
canvas.drawString(infoStr, xLeftOffset + (plotWidth-infoStrWidth*0.707)/2, yTopOffset + \
(plotHeight+infoStrWidth*0.707)/2,font=labelFont, angle = 45, color=pid.red)
labelFont=pid.Font(ttf="verdana",size=12,bold=0)
gifmap = HT.Map(name='markerMap')
lineColor = pid.lightblue
#draw ChrA Loci
ChrAInfo = d[3]
preLpos = -1
i = 0
for item in ChrAInfo:
Lname,Lpos = item
if Lpos != preLpos:
i += 1
preLpos = Lpos
stepA = float(plotWidth)/i
offsetA = -stepA
LRectWidth = 10
LRectHeight = 3
i = 0
preLpos = -1
for item in ChrAInfo:
Lname,Lpos = item
if Lpos != preLpos:
offsetA += stepA
differ = 1
else:
differ = 0
preLpos = Lpos
Lpos *= plotScale
Zorder = i % 5
"""
LStrWidth = canvas.stringWidth(Lname,font=labelFont)
canvas.drawString(Lname,xLeftOffset+offsetA+4,yTopOffset+plotHeight+140,\
font=labelFont,color=pid.blue,angle=90)
canvas.drawLine(xLeftOffset+Lpos,yTopOffset+plotHeight,xLeftOffset+offsetA,\
yTopOffset+plotHeight+25,color=lineColor)
canvas.drawLine(xLeftOffset+offsetA,yTopOffset+plotHeight+25,xLeftOffset+offsetA,\
yTopOffset+plotHeight+140-LStrWidth,color=lineColor)
COORDS="%d,%d,%d,%d"%(xLeftOffset+offsetA+4,yTopOffset+plotHeight+140,\
xLeftOffset+offsetA-6,yTopOffset+plotHeight+140-LStrWidth)
"""
if differ:
canvas.drawLine(xLeftOffset+Lpos,yTopOffset+plotHeight,xLeftOffset+offsetA,\
yTopOffset+plotHeight+25,color=lineColor)
canvas.drawLine(xLeftOffset+offsetA,yTopOffset+plotHeight+25,xLeftOffset+offsetA,\
yTopOffset+plotHeight+80+Zorder*(LRectWidth+3),color=lineColor)
rectColor = pid.orange
else:
canvas.drawLine(xLeftOffset+offsetA, yTopOffset+plotHeight+80+Zorder*(LRectWidth+3)-3,\
xLeftOffset+offsetA, yTopOffset+plotHeight+80+Zorder*(LRectWidth+3),color=lineColor)
rectColor = pid.deeppink
canvas.drawRect(xLeftOffset+offsetA, yTopOffset+plotHeight+80+Zorder*(LRectWidth+3),\
xLeftOffset+offsetA-LRectHeight,yTopOffset+plotHeight+80+Zorder*(LRectWidth+3)+LRectWidth,\
edgeColor=rectColor,fillColor=rectColor,edgeWidth = 0)
COORDS="%d,%d,%d,%d"%(xLeftOffset+offsetA, yTopOffset+plotHeight+80+Zorder*(LRectWidth+3),\
xLeftOffset+offsetA-LRectHeight,yTopOffset+plotHeight+80+Zorder*(LRectWidth+3)+LRectWidth)
HREF="javascript:showTrait('%s','%s');" % (mainfmName, Lname)
Areas=HT.Area(shape='rect',coords=COORDS,href=HREF, title="Locus : " + Lname)
gifmap.areas.append(Areas)
i += 1
#print (i , offsetA, Lname, Lpos, preLpos)
#print "<BR>"
#draw ChrB Loci
ChrBInfo = d[4]
preLpos = -1
i = 0
for item in ChrBInfo:
Lname,Lpos = item
if Lpos != preLpos:
i += 1
preLpos = Lpos
stepB = float(plotHeight)/i
offsetB = -stepB
LRectWidth = 10
LRectHeight = 3
i = 0
preLpos = -1
for item in ChrBInfo:
Lname,Lpos = item
if Lpos != preLpos:
offsetB += stepB
differ = 1
else:
differ = 0
preLpos = Lpos
Lpos *= plotScale
Zorder = i % 5
Lname,Lpos = item
Lpos *= plotScale
"""
LStrWidth = canvas.stringWidth(Lname,font=labelFont)
canvas.drawString(Lname, 45,yTopOffset+plotHeight-offsetB+4,font=labelFont,color=pid.blue)
canvas.drawLine(45+LStrWidth,yTopOffset+plotHeight-offsetB,xLeftOffset-25,\
yTopOffset+plotHeight-offsetB,color=lineColor)
canvas.drawLine(xLeftOffset-25,yTopOffset+plotHeight-offsetB,xLeftOffset,\
yTopOffset+plotHeight-Lpos,color=lineColor)
COORDS = "%d,%d,%d,%d" %(45,yTopOffset+plotHeight-offsetB+4,45+LStrWidth,\
yTopOffset+plotHeight-offsetB-6)
"""
if differ:
canvas.drawLine(xLeftOffset,yTopOffset+plotHeight-Lpos, xLeftOffset-25,\
yTopOffset+plotHeight-offsetB,color=lineColor)
canvas.drawLine(xLeftOffset -25, yTopOffset+plotHeight-offsetB, \
xLeftOffset-80 -Zorder*(LRectWidth+3),yTopOffset+plotHeight-offsetB, color=lineColor)
rectColor = pid.orange
else:
canvas.drawLine(xLeftOffset -80 -Zorder*(LRectWidth+3)+3, yTopOffset+plotHeight-offsetB, \
xLeftOffset-80 -Zorder*(LRectWidth+3),yTopOffset+plotHeight-offsetB, color=lineColor)
rectColor = pid.deeppink
HREF = "javascript:showTrait('%s','%s');" % (mainfmName, Lname)
canvas.drawRect(xLeftOffset-80 -Zorder*(LRectWidth+3),yTopOffset+plotHeight-offsetB,\
xLeftOffset-80 -Zorder*(LRectWidth+3)-LRectWidth,yTopOffset+plotHeight-offsetB +LRectHeight,\
edgeColor=rectColor,fillColor=rectColor,edgeWidth = 0)
COORDS="%d,%d,%d,%d"%(xLeftOffset-80 -Zorder*(LRectWidth+3),yTopOffset+plotHeight-offsetB,\
xLeftOffset-80 -Zorder*(LRectWidth+3)-LRectWidth,yTopOffset+plotHeight-offsetB +LRectHeight)
Areas=HT.Area(shape='rect',coords=COORDS,href=HREF, title="Locus : " + Lname)
gifmap.areas.append(Areas)
i += 1
canvas.drawRect(xLeftOffset, yTopOffset, xLeftOffset+plotWidth, yTopOffset+plotHeight,edgeColor=pid.black)
#draw spectrum
i = 0
labelFont=pid.Font(ttf="tahoma",size=14,bold=0)
middleoffsetX = 80
for dcolor in finecolors:
canvas.drawLine(xLeftOffset+ plotWidth +middleoffsetX-15 , plotHeight + yTopOffset - i, \
xLeftOffset+ plotWidth +middleoffsetX+15 , plotHeight + yTopOffset - i, color=dcolor)
if i % 50 == 0:
if Chr_A >= Chr_B:
canvas.drawLine(xLeftOffset+ plotWidth +middleoffsetX+15 ,plotHeight + yTopOffset - i, \
xLeftOffset+ plotWidth +middleoffsetX+20,plotHeight + yTopOffset - i, color=pid.black)
canvas.drawString('%d' % int(LRSFullThresh*i/250.0),xLeftOffset+ plotWidth +middleoffsetX+22,\
plotHeight + yTopOffset - i +5, font = labelFont,color=pid.black)
if Chr_A <= Chr_B:
canvas.drawLine(xLeftOffset+ plotWidth +middleoffsetX-15 ,plotHeight + yTopOffset - i, \
xLeftOffset+ plotWidth +middleoffsetX-20,plotHeight + yTopOffset - i, color=pid.black)
canvas.drawString('%d' % int(LRSInteractThresh*i/250.0),xLeftOffset+plotWidth+middleoffsetX-40,\
plotHeight + yTopOffset - i +5, font = labelFont,color=pid.black)
i += 1
#draw spectrum label
labelFont2=pid.Font(ttf="verdana",size=20,bold=0)
if i % 50 == 0:
i -= 1
if Chr_A >= Chr_B:
canvas.drawLine(xLeftOffset+ plotWidth +middleoffsetX+15 ,plotHeight + yTopOffset - i, \
xLeftOffset+ plotWidth +middleoffsetX+20,plotHeight + yTopOffset - i, color=pid.black)
canvas.drawString('%d' % int(LRSFullThresh*(i+1)/250.0),xLeftOffset+ plotWidth +middleoffsetX+22,\
plotHeight + yTopOffset - i +5, font = labelFont,color=pid.black)
canvas.drawString('LRS Full',xLeftOffset+ plotWidth +middleoffsetX+50,plotHeight + yTopOffset, \
font = labelFont2,color=pid.dimgray,angle=90)
if Chr_A <= Chr_B:
canvas.drawLine(xLeftOffset+ plotWidth +middleoffsetX-15 ,plotHeight + yTopOffset - i, \
xLeftOffset+ plotWidth +middleoffsetX-20,plotHeight + yTopOffset - i, color=pid.black)
canvas.drawString('%d' % int(LRSInteractThresh*(i+1)/250.0),xLeftOffset+ plotWidth+middleoffsetX-40,\
plotHeight + yTopOffset - i +5, font = labelFont,color=pid.black)
canvas.drawString('LRS Interaction',xLeftOffset+ plotWidth +middleoffsetX-50,\
plotHeight + yTopOffset, font = labelFont2,color=pid.dimgray,angle=90)
filename= webqtlUtil.genRandStr("Pair_")
canvas.save(webqtlConfig.IMGDIR+filename, format='png')
img2=HT.Image('/image/'+filename+'.png',border=0,usemap='#markerMap')
main_title = HT.Paragraph("Pair-Scan Results: Chromosome Pair")
main_title.__setattr__("class","title")
form = HT.Form(cgi = os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), enctype='multipart/form-data', \
name=mainfmName, submit=HT.Input(type='hidden'))
hddn = {'FormID':'showDatabase','ProbeSetID':'_','database':fd.RISet+"Geno",'CellID':'_','RISet':fd.RISet, 'incparentsf1':'on'}
if fd.incparentsf1:
hddn['incparentsf1']='ON'
for key in hddn.keys():
form.append(HT.Input(name=key, value=hddn[key], type='hidden'))
form.append(img2,gifmap)
TD_LR.append(main_title, HT.Center(form), HT.P())
else:
heading = "Direct Plot"
detail = ['Fewer than %d strain data were entered for %s data set. No statitical analysis has been attempted.'\
% (webqtlConfig.KMININFORMATIVE, fd.RISet)]
self.error(heading=heading,detail=detail)
return
self.dict['body'] = str(TD_LR)
