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diff --git a/web/webqtl/heatmap/heatmapPage_GN.py b/web/webqtl/heatmap/heatmapPage_GN.py
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-# Copyright (C) University of Tennessee Health Science Center, Memphis, TN.
-#
-# This program is free software: you can redistribute it and/or modify it
-# under the terms of the GNU Affero General Public License
-# as published by the Free Software Foundation, either version 3 of the
-# License, or (at your option) any later version.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
-# See the GNU Affero General Public License for more details.
-#
-# This program is available from Source Forge: at GeneNetwork Project
-# (sourceforge.net/projects/genenetwork/).
-#
-# Contact Drs. Robert W. Williams and Xiaodong Zhou (2010)
-# at rwilliams@uthsc.edu and xzhou15@uthsc.edu
-#
-#
-#
-# This module is used by GeneNetwork project (www.genenetwork.org)
-#
-# Created by GeneNetwork Core Team 2010/08/10
-#
-# Last updated by GeneNetwork Core Team 2010/10/20
-
-import os
-import string
-import piddle as pid
-import cPickle
-from htmlgen import HTMLgen2 as HT
-
-from base.templatePage import templatePage
-from base import webqtlConfig
-from base.webqtlTrait import webqtlTrait
-from utility import webqtlUtil
-from utility import Plot
-import slink
-
-
-# XZ, 09/09/2008: After adding several traits to collection, click "QTL Heatmap" button,
-# XZ, 09/09/2008: This class will generate what you see.
-#########################################
-# QTL heatmap Page
-#########################################
-class heatmapPage(templatePage):
-
- labelFont=pid.Font(ttf="tahoma",size=14,bold=0)
-
- topHeight = 0
-
- def __init__(self,fd):
-
- templatePage.__init__(self, fd)
-
- if not self.openMysql():
- return
- if not fd.genotype:
- fd.readGenotype()
-
-
- self.searchResult = fd.formdata.getvalue('searchResult')
-
- if not self.searchResult:
- templatePage.__init__(self, fd)
- heading = 'QTL Heatmap'
- detail = ['You need to select at least two traits in order to generate correlation matrix.']
- self.error(heading=heading,detail=detail)
- return
- if type("1") == type(self.searchResult):
- self.searchResult = string.split(self.searchResult,'\t')
-
-
- if self.searchResult:
- if len(self.searchResult) > webqtlConfig.MAXCORR:
- heading = 'QTL Heatmap'
- detail = ['In order to display the QTL heat map properly, do not select more than %d traits for analysis.' % webqtlConfig.MAXCORR]
- self.error(heading=heading,detail=detail)
- return
-
- traitList = []
- traitDataList = []
- for item in self.searchResult:
- thisTrait = webqtlTrait(fullname=item, cursor=self.cursor)
- thisTrait.retrieveInfo()
- thisTrait.retrieveData(fd.strainlist)
- traitList.append(thisTrait)
- traitDataList.append(thisTrait.exportData(fd.strainlist))
- else:
- heading = 'QTL Heatmap'
- detail = [HT.Font('Error : ',color='red'),HT.Font('Error occurs while retrieving data from database.',color='black')]
- self.error(heading=heading,detail=detail)
- return
-
- self.colorScheme = fd.formdata.getvalue('colorScheme')
- if not self.colorScheme:
- self.colorScheme = '1'
-
- self.dict['title'] = 'QTL heatmap'
-
- NNN = len(traitList)
-
- if NNN == 0:
- heading = "QTL Heatmap"
- detail = ['No trait was selected for %s data set. No QTL heatmap was generated.' % fd.RISet]
- self.error(heading=heading,detail=detail)
- return
- elif NNN < 2:
- templatePage.__init__(self, fd)
- heading = 'QTL Heatmap'
- detail = ['You need to select at least two traits in order to generate QTL heatmap.']
- self.error(heading=heading,detail=detail)
- return
- else:
- #XZ: It's necessory to define canvas here
- canvas = pid.PILCanvas(size=(80+NNN*20,880))
-
- names = map(webqtlTrait.displayName, traitList)
-
- self.targetDescriptionChecked = fd.formdata.getvalue('targetDescriptionCheck', '')
-
- #XZ, 7/29/2009: create trait display and find max strWidth
- strWidth = 0
- for j in range(len(names)):
- thisTrait = traitList[j]
-
- if self.targetDescriptionChecked:
- if thisTrait.db.type == 'ProbeSet':
- if thisTrait.probe_target_description:
- names[j] += ' [%s at Chr %s @ %2.3fMB, %s]' % (thisTrait.symbol, thisTrait.chr, thisTrait.mb, thisTrait.probe_target_description)
- else:
- names[j] += ' [%s at Chr %s @ %2.3fMB]' % (thisTrait.symbol, thisTrait.chr, thisTrait.mb)
- elif thisTrait.db.type == 'Geno':
- names[j] += ' [Chr %s @ %2.3fMB]' % (thisTrait.chr, thisTrait.mb)
- elif thisTrait.db.type == 'Publish':
- if thisTrait.abbreviation:
- names[j] += ' [%s]' % (thisTrait.abbreviation)
- else:
- pass
- else:
- pass
-
- i = canvas.stringWidth(names[j],font=self.labelFont)
- if i > strWidth:
- strWidth = i
-
- width = NNN*20
- xoffset = 40
- yoffset = 40
- cellHeight = 3
- nLoci = reduce(lambda x,y: x+y, map(lambda x: len(x),fd.genotype),0)
-
- if nLoci > 2000:
- cellHeight = 1
- elif nLoci > 1000:
- cellHeight = 2
- elif nLoci < 200:
- cellHeight = 10
- else:
- pass
-
- pos = range(NNN)
- neworder = []
- BWs = Plot.BWSpectrum()
- colors100 = Plot.colorSpectrum()
- colors = Plot.colorSpectrum(130)
- finecolors = Plot.colorSpectrum(250)
- colors100.reverse()
- colors.reverse()
- finecolors.reverse()
-
- scaleFont=pid.Font(ttf="tahoma",size=10,bold=0)
-
- self.clusterChecked = fd.formdata.getvalue('clusterCheck', '')
-
-
- if not self.clusterChecked: #XZ: this part is for original order
- for i in range(len(names)):
- neworder.append((xoffset+20*(i+1), i))
-
- canvas = pid.PILCanvas(size=(80+NNN*20+240,80+ self.topHeight +5+5+strWidth+nLoci*cellHeight+80+20*cellHeight))
-
- self.drawTraitNameBottom(canvas,names,yoffset,neworder,strWidth)
- else: #XZ: this part is to cluster traits
- self.topHeight = 400
- canvas = pid.PILCanvas(size=(80+NNN*20+240,80+ self.topHeight +5+5+strWidth+nLoci*cellHeight+80+20*cellHeight))
-
- corArray = [([0] * (NNN))[:] for i in range(NNN)]
-
- nnCorr = len(fd.strainlist)
-
- #XZ, 08/04/2009: I commented out pearsonArray, spearmanArray
- for i, thisTrait in enumerate(traitList):
- names1 = [thisTrait.db.name, thisTrait.name, thisTrait.cellid]
- for j, thisTrait2 in enumerate(traitList):
- names2 = [thisTrait2.db.name, thisTrait2.name, thisTrait2.cellid]
- if j < i:
- corr,nOverlap = webqtlUtil.calCorrelation(traitDataList[i],traitDataList[j],nnCorr)
- if (1-corr) < 0:
- distance = 0.0
- else:
- distance = 1-corr
- corArray[i][j] = distance
- corArray[j][i] = distance
- elif j == i:
- corArray[i][j] = 0.0
- else:
- pass
-
- #XZ, 7/29/2009: The parameter d has info of cluster (group member and distance). The format of d is tricky. Print it out to see it's format.
- d = slink.slink(corArray)
-
- #XZ, 7/29/2009: Attention: The 'neworder' is changed by the 'draw' function
- #XZ, 7/30/2009: Only toppos[1][0] and top[1][1] are used later. Then what toppos[0] is used for?
- toppos = self.draw(canvas,names,d,xoffset,yoffset,neworder)
- self.drawTraitNameTop(canvas,names,yoffset,neworder,strWidth)
-
- #XZ, 7/29/2009: draw the top vertical line
- canvas.drawLine(toppos[1][0],toppos[1][1],toppos[1][0],yoffset)
-
- #XZ: draw string 'distance = 1-r'
- canvas.drawString('distance = 1-r',neworder[-1][0] + 50, self.topHeight*3/4,font=self.labelFont,angle=90)
-
- #draw Scale
- scaleFont=pid.Font(ttf="tahoma",size=10,bold=0)
- x = neworder[-1][0]
- canvas.drawLine(x+5, self.topHeight+yoffset, x+5, yoffset, color=pid.black)
- y = 0
- while y <=2:
- canvas.drawLine(x+5, self.topHeight*y/2.0+yoffset, x+10, self.topHeight*y/2.0+yoffset)
- canvas.drawString('%2.1f' % (2-y), x+12, self.topHeight*y/2.0+yoffset, font=scaleFont)
- y += 0.5
-
-
- chrname = 0
- chrnameFont=pid.Font(ttf="tahoma",size=24,bold=0)
- Ncol = 0
-
- gifmap = HT.Map(name='traitMap')
-
- nearestMarkers = self.getNearestMarker(traitList, fd.genotype)
-
- # import cPickle
- sessionfile = fd.formdata.getvalue("session")
-
- if sessionfile:
- fp = open(os.path.join(webqtlConfig.TMPDIR, sessionfile + '.session'), 'rb')
- permData = cPickle.load(fp)
- fp.close()
- else:
- permData = {}
-
- #XZ, 7/31/2009: This for loop is to generate the heatmap
- #XZ: draw trait by trait instead of marker by marker
- for order in neworder:
- #startHeight = 40+400+5+5+strWidth
- startHeight = self.topHeight + 40+5+5+strWidth
- startWidth = order[0]-5
- if Ncol and Ncol % 5 == 0:
- drawStartPixel = 8
- else:
- drawStartPixel = 9
-
- tempVal = traitDataList[order[1]]
- _vals = []
- _strains = []
- for i in range(len(fd.strainlist)):
- if tempVal[i] != None:
- _strains.append(fd.strainlist[i])
- _vals.append(tempVal[i])
-
- qtlresult = fd.genotype.regression(strains = _strains, trait = _vals)
-
- if sessionfile:
- LRSArray = permData[str(traitList[order[1]])]
- else:
- LRSArray = fd.genotype.permutation(strains = _strains, trait = _vals, nperm = 1000)
- permData[str(traitList[order[1]])] = LRSArray
-
- sugLRS = LRSArray[369]
- sigLRS = LRSArray[949]
- prechr = 0
- chrstart = 0
- nearest = nearestMarkers[order[1]]
- midpoint = []
-
- for item in qtlresult:
- if item.lrs > webqtlConfig.MAXLRS:
- adjustlrs = webqtlConfig.MAXLRS
- else:
- adjustlrs = item.lrs
-
- if item.locus.chr != prechr:
- if prechr:
- canvas.drawRect(startWidth-drawStartPixel, startHeight, startWidth+10, startHeight+3,edgeColor=pid.white, edgeWidth=0, fillColor=pid.white)
- startHeight+= 3
- if not chrname:
- canvas.drawString(prechr,xoffset-20,(chrstart+startHeight)/2,font = chrnameFont,color=pid.dimgray)
- prechr = item.locus.chr
- chrstart = startHeight
- if self.colorScheme == '0':
- if adjustlrs <= sugLRS:
- colorIndex = int(65*adjustlrs/sugLRS)
- else:
- colorIndex = int(65 + 35*(adjustlrs-sugLRS)/(sigLRS-sugLRS))
- if colorIndex > 99:
- colorIndex = 99
- colorIndex = colors100[colorIndex]
- elif self.colorScheme == '1':
- sugLRS = LRSArray[369]/2.0
- if adjustlrs <= sugLRS:
- colorIndex = BWs[20+int(50*adjustlrs/sugLRS)]
- else:
- if item.additive > 0:
- colorIndex = int(80 + 50*(adjustlrs-sugLRS)/(sigLRS-sugLRS))
- else:
- colorIndex = int(50 - 50*(adjustlrs-sugLRS)/(sigLRS-sugLRS))
- if colorIndex > 129:
- colorIndex = 129
- if colorIndex < 0:
- colorIndex = 0
- colorIndex = colors[colorIndex]
- elif self.colorScheme == '2':
- if item.additive > 0:
- colorIndex = int(150 + 100*(adjustlrs/sigLRS))
- else:
- colorIndex = int(100 - 100*(adjustlrs/sigLRS))
- if colorIndex > 249:
- colorIndex = 249
- if colorIndex < 0:
- colorIndex = 0
- colorIndex = finecolors[colorIndex]
- else:
- colorIndex = pid.white
-
- if startHeight > 1:
- canvas.drawRect(startWidth-drawStartPixel, startHeight, startWidth+10, startHeight+cellHeight,edgeColor=colorIndex, edgeWidth=0, fillColor=colorIndex)
- else:
- canvas.drawLine(startWidth-drawStartPixel, startHeight, startWidth+10, startHeight, Color=colorIndex)
-
- if item.locus.name == nearest:
- midpoint = [startWidth,startHeight-5]
- startHeight+=cellHeight
-
- #XZ, map link to trait name and band
- COORDS = "%d,%d,%d,%d" %(startWidth-drawStartPixel,self.topHeight+40,startWidth+10,startHeight)
- HREF = "javascript:showDatabase2('%s','%s','%s');" % (traitList[order[1]].db.name, traitList[order[1]].name, traitList[order[1]].cellid)
- Areas = HT.Area(shape='rect',coords=COORDS,href=HREF, title='%s' % names[order[1]])
- gifmap.areas.append(Areas)
-
- if midpoint:
- traitPixel = ((midpoint[0],midpoint[1]),(midpoint[0]-6,midpoint[1]+12),(midpoint[0]+6,midpoint[1]+12))
- canvas.drawPolygon(traitPixel,edgeColor=pid.black,fillColor=pid.orange,closed=1)
-
- if not chrname:
- canvas.drawString(prechr,xoffset-20,(chrstart+startHeight)/2,font = chrnameFont,color=pid.dimgray)
- chrname = 1
- Ncol += 1
-
-
- #draw Spectrum
- startSpect = neworder[-1][0] + 30
- startHeight = self.topHeight + 40+5+5+strWidth
-
- if self.colorScheme == '0':
- for i in range(100):
- canvas.drawLine(startSpect+i,startHeight+20,startSpect+i,startHeight+40,color=colors100[i])
- scaleFont=pid.Font(ttf="tahoma",size=10,bold=0)
- canvas.drawLine(startSpect,startHeight+45,startSpect,startHeight+39,color=pid.black)
- canvas.drawString('LRS = 0',startSpect,startHeight+55,font=scaleFont)
- canvas.drawLine(startSpect+64,startHeight+45,startSpect+64,startHeight+39,color=pid.black)
- canvas.drawString('Suggestive LRS',startSpect+64,startHeight+55,font=scaleFont)
- canvas.drawLine(startSpect+99,startHeight+45,startSpect+99,startHeight+39,color=pid.black)
- canvas.drawString('Significant LRS',startSpect+105,startHeight+40,font=scaleFont)
- elif self.colorScheme == '1':
- for i in range(50):
- canvas.drawLine(startSpect+i,startHeight,startSpect+i,startHeight+40,color=BWs[20+i])
- for i in range(50,100):
- canvas.drawLine(startSpect+i,startHeight,startSpect+i,startHeight+20,color=colors[100-i])
- canvas.drawLine(startSpect+i,startHeight+20,startSpect+i,startHeight+40,color=colors[30+i])
-
- canvas.drawLine(startSpect,startHeight+45,startSpect,startHeight+39,color=pid.black)
- canvas.drawString('LRS = 0',startSpect,startHeight+60,font=scaleFont)
- canvas.drawLine(startSpect+50,startHeight+45,startSpect+50,startHeight+39,color=pid.black)
- canvas.drawString('0.5*Suggestive LRS',startSpect+50,startHeight+ 60,font=scaleFont)
- canvas.drawLine(startSpect+99,startHeight+45,startSpect+99,startHeight+39,color=pid.black)
- canvas.drawString('Significant LRS',startSpect+105,startHeight+50,font=scaleFont)
- textFont=pid.Font(ttf="verdana",size=18,bold=0)
- canvas.drawString('%s +' % fd.ppolar,startSpect+120,startHeight+ 35,font=textFont,color=pid.red)
- canvas.drawString('%s +' % fd.mpolar,startSpect+120,startHeight+ 15,font=textFont,color=pid.blue)
- elif self.colorScheme == '2':
- for i in range(100):
- canvas.drawLine(startSpect+i,startHeight,startSpect+i,startHeight+20,color=finecolors[100-i])
- canvas.drawLine(startSpect+i,startHeight+20,startSpect+i,startHeight+40,color=finecolors[150+i])
-
- canvas.drawLine(startSpect,startHeight+45,startSpect,startHeight+39,color=pid.black)
- canvas.drawString('LRS = 0',startSpect,startHeight+60,font=scaleFont)
- canvas.drawLine(startSpect+99,startHeight+45,startSpect+99,startHeight+39,color=pid.black)
- canvas.drawString('Significant LRS',startSpect+105,startHeight+50,font=scaleFont)
- textFont=pid.Font(ttf="verdana",size=18,bold=0)
- canvas.drawString('%s +' % fd.ppolar,startSpect+120,startHeight+ 35,font=textFont,color=pid.red)
- canvas.drawString('%s +' % fd.mpolar,startSpect+120,startHeight+ 15,font=textFont,color=pid.blue)
-
-
- filename= webqtlUtil.genRandStr("Heatmap_")
- canvas.save(webqtlConfig.IMGDIR+filename, format='png')
- img2=HT.Image('/image/'+filename+'.png',border=0,usemap='#traitMap')
- imgUrl = 'Right-click or control-click on the link to download this graph as a <a href="/image/%s.png" class="normalsize" target="_blank">PNG file</a>' % filename
-
- form = HT.Form(cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), enctype='multipart/form-data', name='showDatabase', submit=HT.Input(type='hidden'))
- hddn = {'FormID':'showDatabase','ProbeSetID':'_','database':fd.RISet+"Geno",'CellID':'_','RISet':fd.RISet,'searchResult':string.join(self.searchResult,'\t')}
- if fd.incparentsf1:
- hddn['incparentsf1']='ON'
- for key in hddn.keys():
- form.append(HT.Input(name=key, value=hddn[key], type='hidden'))
-
- heatmap = HT.Input(type='button' ,name='mintmap',value='Redraw QTL Heatmap', onClick="databaseFunc(this.form,'heatmap');",Class="button")
- spects = {'0':'Single Spectrum','1':'Grey + Blue + Red','2':'Blue + Red'}
- schemeMenu = HT.Select(name='colorScheme')
- schemeMenu.append(('Single Spectrum',0))
- schemeMenu.append(('Grey + Blue + Red',1))
- schemeMenu.append(('Blue + Red',2))
- schemeMenu.selected.append(spects[self.colorScheme])
-
- clusterCheck= HT.Input(type='checkbox', Class='checkbox', name='clusterCheck',checked=0)
- targetDescriptionCheck = HT.Input(type='checkbox', Class='checkbox', name='targetDescriptionCheck',checked=0)
-
- form.append(gifmap,schemeMenu, heatmap, HT.P(), clusterCheck, ' Cluster traits ', targetDescriptionCheck, ' Add description', HT.P(),img2, HT.P(), imgUrl)
-
- if not sessionfile:
- filename = webqtlUtil.generate_session()
- webqtlUtil.dump_session(permData, os.path.join(webqtlConfig.TMPDIR, filename +'.session'))
- sessionfile=filename
-
- form.append(HT.Input(name='session', value=sessionfile, type='hidden'))
-
- heatmapHelp = HT.Input(type='button' ,name='heatmapHelpButton',value='Info', onClick="openNewWin('/heatmap.html');",Class="button")
-
- heatmapHeading = HT.Paragraph('QTL Heatmap ', heatmapHelp, Class="title")
-
- TD_LR = HT.TD(colspan=2,height=200,width="100%",bgColor='#eeeeee')
- TD_LR.append(heatmapHeading, HT.P(),HT.P(),HT.P(),HT.P(),HT.P(),form)
-
- self.dict['body'] = str(TD_LR)
-
- #XZ, 7/31/2009: This function put the order of traits into parameter neworder,
- #XZ: return the position of the top vertical line of the hierarchical tree, draw the hierarchical tree.
- def draw(self,canvas,names,d,xoffset,yoffset,neworder):
- maxDistance = self.topHeight
- fontoffset = 4 #XZ, 7/31/2009: used only for drawing tree
-
- if type(d[0]) == type(1) and type(d[1]) == type(1):
- neworder.append((xoffset+20,d[0]))
- neworder.append((xoffset+40,d[1]))
- height = d[2]*maxDistance/2
- canvas.drawLine(xoffset+20-fontoffset,maxDistance+yoffset,xoffset+20-fontoffset,maxDistance-height+yoffset)
- canvas.drawLine(xoffset+40-fontoffset,maxDistance+yoffset,xoffset+40-fontoffset,maxDistance-height+yoffset)
- canvas.drawLine(xoffset+40-fontoffset,maxDistance+yoffset-height,xoffset+20-fontoffset,maxDistance-height+yoffset)
- return (40,(xoffset+30-fontoffset,maxDistance-height+yoffset))
- elif type(d[0]) == type(1):
- neworder.append((xoffset+20,d[0]))
- d2 = self.draw(canvas,names,d[1],xoffset+20,yoffset,neworder)
- height = d[2]*maxDistance/2
- canvas.drawLine(xoffset+20-fontoffset,maxDistance+yoffset,xoffset+20-fontoffset,maxDistance-height+yoffset)
- canvas.drawLine(d2[1][0],d2[1][1],d2[1][0],maxDistance-height+yoffset)
- canvas.drawLine(d2[1][0],maxDistance-height+yoffset,xoffset+20-fontoffset,maxDistance-height+yoffset)
- return (20+d2[0],((d2[1][0]+xoffset+20-fontoffset)/2,maxDistance-height+yoffset))
- elif type(d[1]) == type(1):
- d1 = self.draw(canvas,names,d[0],xoffset,yoffset,neworder)
- neworder.append((xoffset+d1[0]+20,d[1]))
- height = d[2]*maxDistance/2
- canvas.drawLine(xoffset+d1[0]+20-fontoffset,maxDistance+yoffset,xoffset+d1[0]+20-fontoffset,maxDistance-height+yoffset)
- canvas.drawLine(d1[1][0],d1[1][1],d1[1][0],maxDistance-height+yoffset)
- canvas.drawLine(d1[1][0],maxDistance-height+yoffset,xoffset+d1[0]+20-fontoffset,maxDistance-height+yoffset)
- return (d1[0]+20,((d1[1][0]+xoffset+d1[0]+20-fontoffset)/2,maxDistance-height+yoffset))
- else:
- d1 = self.draw(canvas,names,d[0],xoffset,yoffset,neworder)
- d2 = self.draw(canvas,names,d[1],xoffset+d1[0],yoffset,neworder)
- height = d[2]*maxDistance/2
- canvas.drawLine(d2[1][0],d2[1][1],d2[1][0],maxDistance-height+yoffset)
- canvas.drawLine(d1[1][0],d1[1][1],d1[1][0],maxDistance-height+yoffset)
- canvas.drawLine(d1[1][0],maxDistance-height+yoffset,d2[1][0],maxDistance-height+yoffset)
- return (d1[0]+d2[0],((d1[1][0]+d2[1][0])/2,maxDistance-height+yoffset))
-
- #XZ, 7/31/2009: dras trait names
- def drawTraitNameBottom (self,canvas,names,yoffset,neworder,strWidth):
- maxDistance = self.topHeight
-
- for oneOrder in neworder:
- canvas.drawString(names[oneOrder[1]],oneOrder[0]-5,maxDistance+yoffset+5+strWidth-canvas.stringWidth(names[oneOrder[1]],font=self.labelFont),font=self.labelFont,color=pid.black,angle=270)
-
- def drawTraitNameTop (self,canvas,names,yoffset,neworder,strWidth):
- maxDistance = self.topHeight
-
- for oneOrder in neworder:
- canvas.drawString(names[oneOrder[1]],oneOrder[0]-5,maxDistance+yoffset+5,font=self.labelFont,color=pid.black,angle=270)
-
-
- def getNearestMarker(self,traitList, genotype):
- out = []
- if not genotype.Mbmap:
- return [None]* len(traitList)
- for item in traitList:
- try:
- nearest = None
- for _chr in genotype:
- if _chr.name != item.chr:
- continue
- distance = 1e30
- for _locus in _chr:
- if abs(_locus.Mb-item.mb) < distance:
- distance = abs(_locus.Mb-item.mb)
- nearest = _locus.name
- out.append(nearest)
- except:
- out.append(None)
-
- return out
-
-
-
-
generated by cgit v1.2.3 (git 2.44.0) at 2024-11-23 19:40:39 +0000