aboutsummaryrefslogtreecommitdiff
path: root/web/webqtl/correlation/PartialCorrDBPage.py
diff options
context:
space:
mode:
Diffstat (limited to 'web/webqtl/correlation/PartialCorrDBPage.py')
-rwxr-xr-xweb/webqtl/correlation/PartialCorrDBPage.py1359
1 files changed, 0 insertions, 1359 deletions
diff --git a/web/webqtl/correlation/PartialCorrDBPage.py b/web/webqtl/correlation/PartialCorrDBPage.py
deleted file mode 100755
index ecd1e623..00000000
--- a/web/webqtl/correlation/PartialCorrDBPage.py
+++ /dev/null
@@ -1,1359 +0,0 @@
-import string
-import cPickle
-import os
-import pyXLWriter as xl
-
-from htmlgen import HTMLgen2 as HT
-
-from base import webqtlConfig
-#import webqtlData
-from utility.THCell import THCell
-from utility.TDCell import TDCell
-from base.webqtlTrait import webqtlTrait
-from base.webqtlDataset import webqtlDataset
-from base.templatePage import templatePage
-from utility import webqtlUtil
-from CorrelationPage import CorrelationPage
-import correlationFunction
-from dbFunction import webqtlDatabaseFunction
-
-
-#########################################
-# Partial Correlation Dataset Page
-#########################################
-
-
-class PartialCorrDBPage(CorrelationPage):
-
- corrMinInformative = 4
-
- def __init__(self, fd):
-
-
- templatePage.__init__(self, fd)
-
- if not self.openMysql():
- return
-
-
- primaryTraitString = fd.formdata.getvalue('primaryTrait')
- primaryTrait = (webqtlTrait(fullname=primaryTraitString, cursor=self.cursor))
-
- controlTraitsString = fd.formdata.getvalue('controlTraits')
- controlTraitsList = list(string.split(controlTraitsString,','))
- controlTraits = []
- for item in controlTraitsList:
- controlTraits.append(webqtlTrait(fullname=item, cursor=self.cursor))
-
- #XZ, 3/16/2010: variable RISet must be pass by the form
- RISet = fd.RISet
- #XZ, 12/12/2008: get species infomation
- species = webqtlDatabaseFunction.retrieveSpecies(cursor=self.cursor, RISet=RISet)
-
- #XZ, 09/18/2008: get all information about the user selected database.
- self.target_db_name = fd.formdata.getvalue('database2')
-
- try:
- self.db = webqtlDataset(self.target_db_name, self.cursor)
- except:
- heading = "Partial Correlation Table"
- detail = ["The database you just requested has not been established yet."]
- self.error(heading=heading,detail=detail)
- return
-
- #XZ, 09/18/2008: check if user has the authority to get access to the database.
- if self.db.type == 'ProbeSet':
- self.cursor.execute('SELECT Id, Name, FullName, confidentiality, AuthorisedUsers FROM ProbeSetFreeze WHERE Name = "%s"' % self.target_db_name)
- indId, indName, indFullName, confidential, AuthorisedUsers = self.cursor.fetchall()[0]
-
- if confidential == 1:
- access_to_confidential_dataset = 0
-
- #for the dataset that confidentiality is 1
- #1. 'admin' and 'root' can see all of the dataset
- #2. 'user' can see the dataset that AuthorisedUsers contains his id(stored in the Id field of User table)
- if webqtlConfig.USERDICT[self.privilege] > webqtlConfig.USERDICT['user']:
- access_to_confidential_dataset = 1
- else:
- AuthorisedUsersList=AuthorisedUsers.split(',')
- if AuthorisedUsersList.__contains__(self.userName):
- access_to_confidential_dataset = 1
-
- if not access_to_confidential_dataset:
- #Error, Confidential Database
- heading = "Partial Correlation Table"
- detail = ["The %s database you selected is not open to the public at this time, please go back and select another database." % indFullName]
- self.error(heading=heading,detail=detail,error="Confidential Database")
- return
-
-
- primaryTrait.retrieveData()
- _primarystrains, _primaryvals, _primaryvars = primaryTrait.exportInformative()
-
- controlTraitNames = fd.formdata.getvalue('controlTraits')
- _controlstrains,_controlvals,_controlvars,_controlNs = correlationFunction.controlStrains(controlTraitNames,_primarystrains)
-
- ## If the strains for which each of the control traits and the primary trait have values are not identical,
- ## we must remove from the calculation all vlaues for strains that are not present in each. Without doing this,
- ## undesirable biases would be introduced.
-
- common_primary_control_strains = _primarystrains #keep _primarystrains
- fixed_primary_vals = _primaryvals #keep _primaryvals
- fixed_control_vals = _controlvals
-
- allsame = True
- ##allsame is boolean for whether or not primary and control trait have values for the same strains
- for i in _controlstrains:
- if _primarystrains != i:
- allsame=False
- break
-
- if not allsame:
- common_primary_control_strains, fixed_primary_vals, fixed_control_vals, _vars, _controlvars = correlationFunction.fixStrains(_primarystrains,_controlstrains,_primaryvals,_controlvals,_primaryvars,_controlvars)
-
- N = len(common_primary_control_strains)
- if N < self.corrMinInformative:
- heading = "Partial Correlation Table"
- detail = ['Fewer than %d strain data were entered for %s data set. No calculation of correlation has been attempted.' % (self.corrMinInformative, RISet)]
- self.error(heading=heading,detail=detail)
- return
-
- #XZ: We should check the value of control trait and primary trait here.
- nameOfIdenticalTraits = correlationFunction.findIdenticalTraits ( fixed_primary_vals, primaryTraitString, fixed_control_vals, controlTraitsList )
- if nameOfIdenticalTraits:
- heading = "Partial Correlation Table"
- detail = ['%s and %s have same values for the %s strains that will be used to calculate partial correlation (common for all primary and control traits). In such case, partial correlation can NOT be calculated. Please re-select your traits.' % (nameOfIdenticalTraits[0], nameOfIdenticalTraits[1], len(fixed_primary_vals))]
- self.error(heading=heading,detail=detail)
- return
-
-
- #XZ, 09/28/2008: if user select "1", then display 1, 3 and 4.
- #XZ, 09/28/2008: if user select "2", then display 2, 3 and 5.
- #XZ, 09/28/2008: if user select "3", then display 1, 3 and 4.
- #XZ, 09/28/2008: if user select "4", then display 1, 3 and 4.
- #XZ, 09/28/2008: if user select "5", then display 2, 3 and 5.
- methodDict = {"1":"Genetic Correlation (Pearson's r)","2":"Genetic Correlation (Spearman's rho)","3":"SGO Literature Correlation","4":"Tissue Correlation (Pearson's r)", "5":"Tissue Correlation (Spearman's rho)"}
- self.method = fd.formdata.getvalue('method')
- if self.method not in ("1","2","3","4","5"):
- self.method = "1"
-
- self.returnNumber = int(fd.formdata.getvalue('criteria'))
-
- myTrait = primaryTrait
- myTrait.retrieveInfo()
-
- # We will not get Literature Correlations if there is no GeneId because there is nothing to look against
- try:
- input_trait_GeneId = myTrait.geneid
- except:
- input_trait_GeneId = None
-
- # We will not get Tissue Correlations if there is no gene symbol because there is nothing to look against
- try:
- input_trait_symbol = myTrait.symbol
- except:
- input_trait_symbol = None
-
-
- #XZ, 12/12/2008: if the species is rat or human, translate the geneid to mouse geneid
- input_trait_mouse_geneid = self.translateToMouseGeneID(species, input_trait_GeneId)
-
- #XZ: As of Nov/13/2010, this dataset is 'UTHSC Illumina V6.2 RankInv B6 D2 average CNS GI average (May 08)'
- TissueProbeSetFreezeId = 1
-
-
- #XZ, 09/22/2008: If we need search by GeneId,
- #XZ, 09/22/2008: we have to check if this GeneId is in the literature or tissue correlation table.
- #XZ, 10/15/2008: We also to check if the selected database is probeset type.
- if self.method == "3" or self.method == "4" or self.method == "5":
- if self.db.type != "ProbeSet":
- self.error(heading="Wrong correlation type",detail="It is not possible to compute the %s between your trait and data in this %s database. Please try again after selecting another type of correlation." % (methodDict[self.method],self.db.name),error="Correlation Type Error")
- return
-
- """
- if not input_trait_GeneId:
- self.error(heading="No Associated GeneId",detail="This trait has no associated GeneId, so we are not able to show any literature or tissue related information.",error="No GeneId Error")
- return
- """
-
- #XZ: We have checked geneid did exist
-
- if self.method == "3":
- if not input_trait_GeneId or not self.checkForLitInfo(input_trait_mouse_geneid):
- self.error(heading="No Literature Info",detail="This gene does not have any associated Literature Information.",error="Literature Correlation Error")
- return
-
- if self.method == "4" or self.method == "5":
- if not input_trait_symbol:
- self.error(heading="No Tissue Correlation Information",detail="This gene does not have any associated Tissue Correlation Information.",error="Tissue Correlation Error")
- return
-
- if not self.checkSymbolForTissueCorr(TissueProbeSetFreezeId, myTrait.symbol):
- self.error(heading="No Tissue Correlation Information",detail="This gene does not have any associated Tissue Correlation Information.",error="Tissue Correlation Error")
- return
-
-#######################################################################################################################################
-
- nnCorr = len(fixed_primary_vals)
-
- #XZ: Use the fast method only for probeset dataset, and this dataset must have been created.
- #XZ: Otherwise, use original method
-
- useFastMethod = False
-
- if self.db.type == "ProbeSet":
- DatabaseFileName = self.getFileName( target_db_name=self.target_db_name )
- DirectoryList = os.listdir(webqtlConfig.TEXTDIR) # List of existing text files. Used to check if a text file already exists
- if DatabaseFileName in DirectoryList:
- useFastMethod = True
-
- if useFastMethod:
- totalTraits, allcorrelations = self.getPartialCorrelationsFast(common_primary_control_strains , fixed_primary_vals, fixed_control_vals, nnCorr, DatabaseFileName, species, input_trait_GeneId, input_trait_symbol, TissueProbeSetFreezeId)
-
- if totalTraits == 0:
- useFastMethod = False
-
- #XZ, 01/08/2009: use the original method to retrieve from database and compute.
- if not useFastMethod:
- totalTraits, allcorrelations = self.getPartialCorrelationsNormal(common_primary_control_strains, fixed_primary_vals, fixed_control_vals, nnCorr, species, input_trait_GeneId, input_trait_symbol,TissueProbeSetFreezeId)
-
-#############################################################
-
- if self.method == "3" and input_trait_GeneId:
- allcorrelations.sort(self.cmpLitCorr)
- elif self.method in ["4","5"] and input_trait_GeneId:
- allcorrelations.sort(self.cmpLitCorr)
- else:
- allcorrelations.sort(self.cmpPartialCorrPValue)
-
- #XZ, 09/20/2008: we only need the top ones.
- self.returnNumber = min(self.returnNumber,len(allcorrelations))
- allcorrelations = allcorrelations[:self.returnNumber]
-
- addLiteratureCorr = False
- addTissueCorr = False
-
- traitList = []
- for item in allcorrelations:
- thisTrait = webqtlTrait(db=self.db, name=item[0], cursor=self.cursor)
- thisTrait.retrieveInfo()
-
- thisTrait.Name = item[0]
- thisTrait.NOverlap = item[1]
-
- thisTrait.partial_corr = item[2]
- thisTrait.partial_corrPValue = item[3]
-
- thisTrait.corr = item[4]
- thisTrait.corrPValue = item[5]
- # NL, 07/19/2010
- # js function changed, add a new parameter rankOrder for js function 'showTissueCorrPlot'
- rankOrder = 0;
- if self.method in ["2","5"]:
- rankOrder = 1;
- thisTrait.rankOrder = rankOrder
-
- #XZ, 26/09/2008: Method is 4 or 5. Have fetched tissue corr, but no literature correlation yet.
- if len(item) == 8:
- thisTrait.tissueCorr = item[6]
- thisTrait.tissuePValue = item[7]
- addLiteratureCorr = True
-
- #XZ, 26/09/2008: Method is 3, Have fetched literature corr, but no tissue corr yet.
- elif len(item) == 7:
- thisTrait.LCorr = item[6]
- thisTrait.mouse_geneid = self.translateToMouseGeneID(species, thisTrait.geneid)
- addTissueCorr = True
-
- #XZ, 26/09/2008: Method is 1 or 2. Have NOT fetched literature corr and tissue corr yet.
- # Phenotype data will not have geneid, and neither will some probes
- # we need to handle this because we will get an attribute error
- else:
- if input_trait_mouse_geneid and self.db.type=="ProbeSet":
- addLiteratureCorr = True
- if input_trait_symbol and self.db.type=="ProbeSet":
- addTissueCorr = True
-
- traitList.append(thisTrait)
-
- if addLiteratureCorr:
- traitList = self.getLiteratureCorrelationByList(input_trait_mouse_geneid, species, traitList)
- if addTissueCorr:
- traitList = self.getTissueCorrelationByList(primaryTraitSymbol=input_trait_symbol, traitList=traitList,TissueProbeSetFreezeId=TissueProbeSetFreezeId, method=self.method)
-
-########################################################
-
- TD_LR = HT.TD(height=200,width="100%",bgColor='#eeeeee')
-
- mainfmName = webqtlUtil.genRandStr("fm_")
- 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':self.target_db_name, 'CellID':'_', 'RISet':RISet, 'identification':fd.identification}
-
- if myTrait:
- hddn['fullname']=str(myTrait)
-
-
- for key in hddn.keys():
- form.append(HT.Input(name=key, value=hddn[key], type='hidden'))
-
- #XZ, 11/21/2008: add two parameters to form
- form.append(HT.Input(name="X_geneSymbol", value="", type='hidden'))
- form.append(HT.Input(name="Y_geneSymbol", value="", type='hidden'))
-
- #XZ, 3/11/2010: add one parameter to record if the method is rank order.
-
- form.append(HT.Input(name="rankOrder", value="%s" % rankOrder, type='hidden'))
-
- form.append(HT.Input(name="TissueProbeSetFreezeId", value="%s" % TissueProbeSetFreezeId, type='hidden'))
-
-
- ####################################
- # generate the info on top of page #
- ####################################
-
- info_form = self.getFormForPrimaryAndControlTraits (primaryTrait, controlTraits)
- info = self.getTopInfo(myTrait=myTrait, method=self.method, db=self.db, target_db_name=self.target_db_name, returnNumber=self.returnNumber, methodDict=methodDict, totalTraits=totalTraits, identification=fd.identification )
-
- ##############
- # Excel file #
- ##############
- filename= webqtlUtil.genRandStr("Corr_")
- xlsUrl = HT.Input(type='button', value = 'Download Table', onClick= "location.href='/tmp/%s.xls'" % filename, Class='button')
- # Create a new Excel workbook
- workbook = xl.Writer('%s.xls' % (webqtlConfig.TMPDIR+filename))
- headingStyle = workbook.add_format(align = 'center', bold = 1, border = 1, size=13, fg_color = 0x1E, color="white")
-
- #XZ, 3/18/2010: pay attention to the line number of header in this file. As of today, there are 7 lines.
- worksheet = self.createExcelFileWithTitleAndFooter(workbook=workbook, identification=fd.identification, db=self.db, returnNumber=self.returnNumber)
-
- newrow = 7
-
-
-
-#####################################################################
-
- mintmap = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'showIntMap');" % mainfmName)
- mintmap_img = HT.Image("/images/multiple_interval_mapping1_final.jpg", name='mintmap', alt="Multiple Interval Mapping", title="Multiple Interval Mapping", style="border:none;")
- mintmap.append(mintmap_img)
- mcorr = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'compCorr');" % mainfmName)
- mcorr_img = HT.Image("/images/compare_correlates2_final.jpg", alt="Compare Correlates", title="Compare Correlates", style="border:none;")
- mcorr.append(mcorr_img)
- cormatrix = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'corMatrix');" % mainfmName)
- cormatrix_img = HT.Image("/images/correlation_matrix1_final.jpg", alt="Correlation Matrix and PCA", title="Correlation Matrix and PCA", style="border:none;")
- cormatrix.append(cormatrix_img)
- networkGraph = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'networkGraph');" % mainfmName)
- networkGraph_img = HT.Image("/images/network_graph1_final.jpg", name='mintmap', alt="Network Graphs", title="Network Graphs", style="border:none;")
- networkGraph.append(networkGraph_img)
- heatmap = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'heatmap');" % mainfmName)
- heatmap_img = HT.Image("/images/heatmap2_final.jpg", name='mintmap', alt="QTL Heat Map and Clustering", title="QTL Heatmap and Clustering", style="border:none;")
- heatmap.append(heatmap_img)
- partialCorr = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'partialCorrInput');" % mainfmName)
- partialCorr_img = HT.Image("/images/partial_correlation_final.jpg", name='partialCorr', alt="Partial Correlation", title="Partial Correlation", style="border:none;")
- partialCorr.append(partialCorr_img)
- addselect = HT.Href(url="#redirect", onClick="addRmvSelection('%s', document.getElementsByName('%s')[0], 'addToSelection');" % (RISet, mainfmName))
- addselect_img = HT.Image("/images/add_collection1_final.jpg", name="addselect", alt="Add To Collection", title="Add To Collection", style="border:none;")
- addselect.append(addselect_img)
- selectall = HT.Href(url="#redirect", onClick="checkAll(document.getElementsByName('%s')[0]);" % mainfmName)
- selectall_img = HT.Image("/images/select_all2_final.jpg", name="selectall", alt="Select All", title="Select All", style="border:none;")
- selectall.append(selectall_img)
- selectinvert = HT.Href(url="#redirect", onClick = "checkInvert(document.getElementsByName('%s')[0]);" % mainfmName)
- selectinvert_img = HT.Image("/images/invert_selection2_final.jpg", name="selectinvert", alt="Invert Selection", title="Invert Selection", style="border:none;")
- selectinvert.append(selectinvert_img)
- reset = HT.Href(url="#redirect", onClick="checkNone(document.getElementsByName('%s')[0]); return false;" % mainfmName)
- reset_img = HT.Image("/images/select_none2_final.jpg", alt="Select None", title="Select None", style="border:none;")
- reset.append(reset_img)
- selecttraits = HT.Input(type='button' ,name='selecttraits',value='Select Traits', onClick="checkTraits(this.form);",Class="button")
- selectgt = HT.Input(type='text' ,name='selectgt',value='-1.0', size=6,maxlength=10,onChange="checkNumeric(this,1.0,'-1.0','gthan','greater than filed')")
- selectlt = HT.Input(type='text' ,name='selectlt',value='1.0', size=6,maxlength=10,onChange="checkNumeric(this,-1.0,'1.0','lthan','less than field')")
- selectandor = HT.Select(name='selectandor')
- selectandor.append(('AND','and'))
- selectandor.append(('OR','or'))
- selectandor.selected.append('AND')
-
- chrMenu = HT.Input(type='hidden',name='chromosomes',value='all')
-
- corrHeading = HT.Paragraph('Partial Correlation Table', Class="title")
-
-
- pageTable = HT.TableLite(cellSpacing=0,cellPadding=0,width="100%", border=0, align="Left")
- containerTable = HT.TableLite(cellSpacing=0,cellPadding=0,width="90%",border=0, align="Left")
-
- optionsTable = HT.TableLite(cellSpacing=2, cellPadding=0,width="320", height="80", border=0, align="Left")
- optionsTable.append(HT.TR(HT.TD(selectall), HT.TD(reset), HT.TD(selectinvert), HT.TD(addselect), align="left"))
- optionsTable.append(HT.TR(HT.TD("&nbsp;"*1,"Select"), HT.TD("Deselect"), HT.TD("&nbsp;"*1,"Invert"), HT.TD("&nbsp;"*3,"Add")))
- containerTable.append(HT.TR(HT.TD(optionsTable)))
-
- functionTable = HT.TableLite(cellSpacing=2,cellPadding=0,width="480",height="80", border=0, align="Left")
- functionRow = HT.TR(HT.TD(networkGraph, width="16.7%"), HT.TD(cormatrix, width="16.7%"), HT.TD(partialCorr, width="16.7%"), HT.TD(mcorr, width="16.7%"), HT.TD(mintmap, width="16.7%"), HT.TD(heatmap), align="left")
- labelRow = HT.TR(HT.TD("&nbsp;"*1,HT.Text("Graph")), HT.TD("&nbsp;"*1,HT.Text("Matrix")), HT.TD("&nbsp;"*1,HT.Text("Partial")), HT.TD(HT.Text("Compare")), HT.TD(HT.Text("QTL Map")), HT.TD(HT.Text(text="Heat Map")))
- functionTable.append(functionRow, labelRow)
- containerTable.append(HT.TR(HT.TD(functionTable), HT.BR()))
-
- moreOptions = HT.Input(type='button',name='options',value='More Options', onClick="",Class="toggle")
- fewerOptions = HT.Input(type='button',name='options',value='Fewer Options', onClick="",Class="toggle")
-
- if (fd.formdata.getvalue('showHideOptions') == 'less'):
- containerTable.append(HT.TR(HT.TD("&nbsp;"), height="10"), HT.TR(HT.TD(HT.Div(fewerOptions, Class="toggleShowHide"))))
- containerTable.append(HT.TR(HT.TD("&nbsp;")))
- else:
- containerTable.append(HT.TR(HT.TD("&nbsp;"), height="10"), HT.TR(HT.TD(HT.Div(moreOptions, Class="toggleShowHide"))))
- containerTable.append(HT.TR(HT.TD("&nbsp;")))
-
- containerTable.append(HT.TR(HT.TD(HT.Span(selecttraits,' with partial r > ',selectgt, ' ',selectandor, ' r < ',selectlt,Class="bd1 cbddf fs11")), style="display:none;", Class="extra_options"))
-
-
- tblobj = {}
-
-
- if self.db.type=="Geno":
-
- containerTable.append(HT.TR(HT.TD(xlsUrl, height=40)))
- pageTable.append(HT.TR(HT.TD(containerTable)))
-
- tblobj['header'], worksheet = self.getTableHeaderForGeno( method=self.method, worksheet=worksheet, newrow=newrow, headingStyle=headingStyle)
- newrow += 1
-
- corrScript = HT.Script(language="Javascript")
- corrScript.append("var corrArray = new Array();")
-
- sortby = self.getSortByValue( calculationMethod = self.method )
-
- tblobj['body'], worksheet, corrScript = self.getTableBodyForGeno(traitList=traitList, formName=mainfmName, worksheet=worksheet, newrow=newrow, corrScript=corrScript)
-
- workbook.close()
- objfile = open('%s.obj' % (webqtlConfig.TMPDIR+filename), 'wb')
- cPickle.dump(tblobj, objfile)
- objfile.close()
- # NL, 07/27/2010. genTableObj function has been moved from templatePage.py to webqtlUtil.py;
- div = HT.Div(webqtlUtil.genTableObj(tblobj=tblobj, file=filename, sortby=sortby, tableID = "sortable", addIndex = "1"), corrScript, Id="sortable")
- pageTable.append(HT.TR(HT.TD(div)))
- form.append(HT.Input(name='ShowStrains',type='hidden', value =1),
- HT.Input(name='ShowLine',type='hidden', value =1),
- HT.P(),pageTable)
-
- TD_LR.append(corrHeading, info_form, HT.P(), info, form, HT.P())
-
- self.dict['body'] = str(TD_LR)
- # updated by NL. Delete function generateJavaScript, move js files to dhtml.js, webqtl.js and jqueryFunction.js
- self.dict['js1'] = ''
- self.dict['title'] = 'Partial Correlation Result'
-
- elif self.db.type=="Publish":
-
- containerTable.append(HT.TR(HT.TD(xlsUrl, height=40)))
- pageTable.append(HT.TR(HT.TD(containerTable)))
-
- tblobj['header'], worksheet = self.getTableHeaderForPublish(method=self.method, worksheet=worksheet, newrow=newrow, headingStyle=headingStyle)
- newrow += 1
-
- sortby = self.getSortByValue( calculationMethod = self.method )
-
- corrScript = HT.Script(language="Javascript")
- corrScript.append("var corrArray = new Array();")
-
- tblobj['body'], worksheet, corrScript = self.getTableBodyForPublish(traitList=traitList, formName=mainfmName, worksheet=worksheet, newrow=newrow, corrScript=corrScript)
-
- workbook.close()
-
- objfile = open('%s.obj' % (webqtlConfig.TMPDIR+filename), 'wb')
- cPickle.dump(tblobj, objfile)
- objfile.close()
- # NL, 07/27/2010. genTableObj function has been moved from templatePage.py to webqtlUtil.py;
- div = HT.Div(webqtlUtil.genTableObj(tblobj=tblobj, file=filename, sortby=sortby, tableID = "sortable", addIndex = "1"), corrScript, Id="sortable")
- pageTable.append(HT.TR(HT.TD(div)))
-
- form.append(
- HT.Input(name='ShowStrains',type='hidden', value =1),
- HT.Input(name='ShowLine',type='hidden', value =1),
- HT.P(),pageTable)
-
- TD_LR.append(corrHeading, info_form, HT.P(), info, form, HT.P())
-
- self.dict['body'] = str(TD_LR)
- #updated by NL. Delete function generateJavaScript, move js files to dhtml.js, webqtl.js and jqueryFunction.js
- self.dict['js1'] = ''
- self.dict['title'] = 'Partial Correlation Result'
-
- elif self.db.type=="ProbeSet":
-
- tblobj['header'], worksheet = self.getTableHeaderForProbeSet(method=self.method, worksheet=worksheet, newrow=newrow, headingStyle=headingStyle)
- newrow += 1
-
- sortby = self.getSortByValue( calculationMethod = self.method )
-
- corrScript = HT.Script(language="Javascript")
- corrScript.append("var corrArray = new Array();")
-
- tblobj['body'], worksheet, corrScript = self.getTableBodyForProbeSet(traitList=traitList, primaryTrait=myTrait, formName=mainfmName, worksheet=worksheet, newrow=newrow, corrScript=corrScript)
-
- workbook.close()
- objfile = open('%s.obj' % (webqtlConfig.TMPDIR+filename), 'wb')
- cPickle.dump(tblobj, objfile)
- objfile.close()
-
- '''
- #XZ, 07/07/2010: I comment out this block of code.
- WebGestaltScript = HT.Script(language="Javascript")
- WebGestaltScript.append("""
-setTimeout('openWebGestalt()', 2000);
-function openWebGestalt(){
- var thisForm = document['WebGestalt'];
- makeWebGestaltTree(thisForm, '%s', %d, 'edag_only.php');
-}
- """ % (mainfmName, len(traitList)))
- '''
-
- #XZ: here is the table of traits
- # NL, 07/27/2010. genTableObj function has been moved from templatePage.py to webqtlUtil.py;
- div = HT.Div(webqtlUtil.genTableObj(tblobj=tblobj, file=filename, sortby=sortby, tableID = "sortable", addIndex = "1"), corrScript, Id="sortable")
-
- self.cursor.execute('SELECT GeneChip.GO_tree_value FROM GeneChip, ProbeFreeze, ProbeSetFreeze WHERE GeneChip.Id = ProbeFreeze.ChipId and ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and ProbeSetFreeze.Name = "%s"' % self.db.name)
- result = self.cursor.fetchone()
-
- if result:
- GO_tree_value = result[0]
-
- if GO_tree_value:
-
- hddnWebGestalt = {
- 'id_list':'',
- 'correlation':'',
- 'id_value':'',
- 'llid_list':'',
- 'id_type':GO_tree_value,
- 'idtype':'',
- 'species':'',
- 'list':'',
- 'client':''}
-
- hddnWebGestalt['ref_type'] = hddnWebGestalt['id_type']
- hddnWebGestalt['cat_type'] = 'GO'
- hddnWebGestalt['significancelevel'] = 'Top10'
-
- if species == 'rat':
- hddnWebGestalt['org'] = 'Rattus norvegicus'
- elif species == 'human':
- hddnWebGestalt['org'] = 'Homo sapiens'
- elif species == 'mouse':
- hddnWebGestalt['org'] = 'Mus musculus'
- else:
- hddnWebGestalt['org'] = ''
-
- for key in hddnWebGestalt.keys():
- form.append(HT.Input(name=key, value=hddnWebGestalt[key], type='hidden'))
-
- #XZ, 01/12/2009: create database menu for 'Add Correlation'
- self.cursor.execute("""
- select
- ProbeSetFreeze.FullName, ProbeSetFreeze.Id, Tissue.name
- from
- ProbeSetFreeze, ProbeFreeze, ProbeSetFreeze as ps2, ProbeFreeze as p2, Tissue
- where
- ps2.Id = %d
- and ps2.ProbeFreezeId = p2.Id
- and ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id
- and (ProbeFreeze.InbredSetId = p2.InbredSetId or (ProbeFreeze.InbredSetId in (1, 3) and p2.InbredSetId in (1, 3)))
- and p2.ChipId = ProbeFreeze.ChipId
- and ps2.Id != ProbeSetFreeze.Id
- and ProbeFreeze.TissueId = Tissue.Id
- and ProbeSetFreeze.public > %d
- order by
- ProbeFreeze.TissueId, ProbeSetFreeze.CreateTime desc
- """ % (self.db.id, webqtlConfig.PUBLICTHRESH))
-
- results = self.cursor.fetchall()
- dbCustomizer = HT.Select(results, name = "customizer")
- databaseMenuSub = preTissue = ""
- for item in results:
- TName, TId, TTissue = item
- if TTissue != preTissue:
- if databaseMenuSub:
- dbCustomizer.append(databaseMenuSub)
- databaseMenuSub = HT.Optgroup(label = '%s mRNA ------' % TTissue)
- preTissue = TTissue
-
- databaseMenuSub.append(item[:2])
- if databaseMenuSub:
- dbCustomizer.append(databaseMenuSub)
- #updated by NL. Delete function generateJavaScript, move js files to dhtml.js, webqtl.js and jqueryFunction.js
- #variables: filename, strainIds and vals are required by getquerystring function
- strainIds=self.getStrainIds(species=species, strains=_primarystrains)
- var1 = HT.Input(name="filename", value=filename, type='hidden')
- var2 = HT.Input(name="strainIds", value=strainIds, type='hidden')
- var3 = HT.Input(name="vals", value=_primaryvals, type='hidden')
- customizerButton = HT.Input(type="button", Class="button", value="Add Correlation", onClick = "xmlhttpPost('%smain.py?FormID=AJAX_table', 'sortable', (getquerystring(this.form)))" % webqtlConfig.CGIDIR)
-
- containerTable.append(HT.TR(HT.TD(HT.Span(var1,var2,var3,customizerButton, "with", dbCustomizer, Class="bd1 cbddf fs11"), HT.BR(), HT.BR()), style="display:none;", Class="extra_options"))
-
- #outside analysis part
- GCATButton = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'GCAT');" % mainfmName)
- GCATButton_img = HT.Image("/images/GCAT_logo_final.jpg", name="GCAT", alt="GCAT", title="GCAT", style="border:none")
- GCATButton.append(GCATButton_img)
-
- ODE = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'ODE');" % mainfmName)
- ODE_img = HT.Image("/images/ODE_logo_final.jpg", name="ode", alt="ODE", title="ODE", style="border:none")
- ODE.append(ODE_img)
-
- WebGestalt = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'GOTree');" % mainfmName)
- WebGestalt_img = HT.Image("/images/webgestalt_icon_final.jpg", name="webgestalt", alt="Gene Set Analysis Toolkit", title="Gene Set Analysis Toolkit", style="border:none")
- WebGestalt.append(WebGestalt_img)
-
- LinkOutTable = HT.TableLite(cellSpacing=2,cellPadding=0,width="320",height="80", border=0, align="Left")
- if not GO_tree_value:
- LinkOutRow = HT.TR(HT.TD(GCATButton, width="50%"), HT.TD(ODE, width="50%"), align="left")
- LinkOutLabels = HT.TR(HT.TD("&nbsp;", HT.Text("GCAT"), width="50%"), HT.TD("&nbsp;",HT.Text("ODE"), width="50%"), align="left")
- else:
- LinkOutRow = HT.TR(HT.TD(WebGestalt, width="25%"), HT.TD(GCATButton, width="25%"), HT.TD(ODE, width="25%"), align="left")
- LinkOutLabels = HT.TR(HT.TD(HT.Text("Gene Set")), HT.TD("&nbsp;"*2, HT.Text("GCAT")), HT.TD("&nbsp;"*3, HT.Text("ODE")), style="display:none;", Class="extra_options")
- LinkOutTable.append(LinkOutRow,LinkOutLabels)
-
- containerTable.append(HT.TR(HT.TD(LinkOutTable), Class="extra_options", style="display:none;"))
-
- containerTable.append(HT.TR(HT.TD(xlsUrl, HT.BR(), HT.BR(), height=40)))
-
- pageTable.append(HT.TR(HT.TD(containerTable)))
-
- pageTable.append(HT.TR(HT.TD(div)))
-
- if species == 'human':
- heatmap = ""
-
- form.append(HT.Input(name='ShowStrains',type='hidden', value =1),
- HT.Input(name='ShowLine',type='hidden', value =1),
- info, HT.BR(), pageTable, HT.BR())
-
- TD_LR.append(corrHeading, info_form, HT.P(), form, HT.P())
-
-
- self.dict['body'] = str(TD_LR)
- self.dict['title'] = 'Partial Correlation Result'
- # updated by NL. Delete function generateJavaScript, move js files to dhtml.js, webqtl.js and jqueryFunction.js
- self.dict['js1'] = ''
- self.dict['js2'] = 'onLoad="pageOffset()"'
- self.dict['layer'] = self.generateWarningLayer()
-
- else:
- self.dict['body'] = ""
-
-
-
-####################################
-# #
-#Partial CorrelationPage Functions #
-# #
-####################################
-
-
- def getSortByValue(self, calculationMethod):
-
- sortby = ("partial_pv", "up")
-
- if calculationMethod == "3": #XZ: literature correlation
- sortby = ("lcorr","down")
- elif calculationMethod == "4" or calculationMethod == "5": #XZ: tissue correlation
- sortby = ("tissuecorr", "down")
-
- return sortby
-
-
- #XZ, 3/31/2010:
- #A[0] holds trait name.
- #A[1] holds partial correlation coefficient number.
- #A[2] holds N.
- #A[3] holds p value of partial correlation.
- def cmpPartialCorrPValue (self, A, B):
- try:
- if A[3] < B[3]:
- return -1
- elif A[3] == B[3]:
- return 0
- else:
- return 1
- except:
- return 0
-
-
- #XZ, 4/1/2010:
- #A[0] holds trait name.
- #A[1] holds N.
- #A[2] holds partial correlation coefficient number.
- #A[3] holds p value of partial correlation.
- #A[6] holds literature corr or tissue corr value.
- #Sort by literature corr or tissue corr first, then by partial corr p value.
- def cmpLitCorr(self, A, B):
- try:
- if abs(A[6]) < abs(B[6]):
- return 1
- elif abs(A[6]) == abs(B[6]):
- if A[3] < B[3]:
- return -1
- elif A[3] == B[3]:
- return 0
- else:
- return 1
- else:
- return -1
- except:
- return 0
-
-
- def getPartialCorrelationsFast(self, _strains, _vals, _controlvals, nnCorr, DatabaseFileName, species, input_trait_GeneId,gene_symbol,TissueProbeSetFreezeId ):
- """Calculates and returns correlation coefficients using data from a csv text file."""
-
- try:
- allcorrelations = []
-
- useLit = False
- if self.method == "3":
- litCorrs = self.fetchLitCorrelations(species=species, GeneId=input_trait_GeneId, db=self.db, returnNumber=self.returnNumber)
- useLit = True
-
- useTissueCorr = False
- if self.method == "4" or self.method == "5":
- tissueCorrs = self.fetchTissueCorrelations(db=self.db,primaryTraitSymbol=gene_symbol, TissueProbeSetFreezeId=TissueProbeSetFreezeId, method=self.method, returnNumber=self.returnNumber)
- useTissueCorr = True
-
- datasetFile = open(webqtlConfig.TEXTDIR+DatabaseFileName,'r')
-
- #XZ, 01/08/2009: read the first line
- line = datasetFile.readline()
- dataset_strains = webqtlUtil.readLineCSV(line)[1:]
-
- #XZ, 3/30/2010: This step is critical.
- good_dataset_strains_index = []
-
- for i in range(len(_strains)):
- found_in_dataset_strains = 0
- for j, one_dataset_strain in enumerate(dataset_strains):
- if one_dataset_strain == _strains[i]:
- found_in_dataset_strains = 1
- good_dataset_strains_index.append(j)
- break
-
- if not found_in_dataset_strains:
- good_dataset_strains_index.append(-99999)
-
- allTargetTraitNames = []
- allTargetTraitValues = []
-
- #XZ, 04/01/2009: If literature corr or tissue corr is selected,
- #XZ: there is no need to compute partial correlation for all traits.
- #XZ: If genetic corr is selected, compute partial correlation for all traits.
- for line in datasetFile:
- trait_line = webqtlUtil.readLineCSV(line)
- trait_name = trait_line[0]
- trait_data = trait_line[1:]
-
- if useLit:
- if not litCorrs.has_key( trait_name ):
- continue
-
- if useTissueCorr:
- if not tissueCorrs.has_key( trait_name ):
- continue
-
- #XZ, 04/01/2010: If useLit or useTissueCorr, and this trait should not be added,
- #it will not go to the next step.
-
- good_dataset_vals = []
- for i in good_dataset_strains_index:
- if i == -99999:
- good_dataset_vals.append(None)
- else:
- good_dataset_vals.append( float(trait_data[i]) )
-
- allTargetTraitNames.append(trait_name)
- allTargetTraitValues.append(good_dataset_vals)
-
- datasetFile.close()
-
- if self.method in ["2", "5"]: #Spearman
- allcorrelations = correlationFunction.determinePartialsByR(primaryVal=_vals, controlVals=_controlvals, targetVals=allTargetTraitValues, targetNames=allTargetTraitNames, method='s')
- else:
- allcorrelations = correlationFunction.determinePartialsByR(primaryVal=_vals, controlVals=_controlvals, targetVals=allTargetTraitValues, targetNames=allTargetTraitNames)
-
- totalTraits = len(allcorrelations)
-
- if useLit or useTissueCorr:
- for i, item in enumerate(allcorrelations):
- if useLit:
- allcorrelations[i].append(litCorrs[ item[0] ])
- if useTissueCorr:
- tempCorr, tempPValue = tissueCorrs[ item[0] ]
- allcorrelations[i].append(tempCorr)
- allcorrelations[i].append(tempPValue)
-
- return totalTraits, allcorrelations
- except:
- return 0, 0
-
-
- def getPartialCorrelationsNormal(self, _strains, _vals, _controlvals, nnCorr, species, input_trait_GeneId, input_trait_symbol,TissueProbeSetFreezeId):
- """Calculates and returns correlation coefficients"""
-
- traitdatabase, dataStartPos = self.fetchAllDatabaseData(species=species, GeneId=input_trait_GeneId, GeneSymbol=input_trait_symbol, strains=_strains, db=self.db, method=self.method, returnNumber=self.returnNumber, tissueProbeSetFreezeId=TissueProbeSetFreezeId)
- totalTraits = len(traitdatabase) #XZ, 09/18/2008: total trait number
-
- allcorrelations = []
-
- allTargetTraitNames = []
- allTargetTraitValues = []
-
- for traitdata in traitdatabase:
- traitdataName = traitdata[0]
- traitvals = traitdata[dataStartPos:]
- allTargetTraitNames.append (traitdataName)
- allTargetTraitValues.append (traitvals)
-
- if self.method in ["2", "5"]: #Spearman
- allcorrelations = correlationFunction.determinePartialsByR(primaryVal=_vals, controlVals=_controlvals, targetVals=allTargetTraitValues, targetNames=allTargetTraitNames, method='s')
- else:
- allcorrelations = correlationFunction.determinePartialsByR(primaryVal=_vals, controlVals=_controlvals, targetVals=allTargetTraitValues, targetNames=allTargetTraitNames)
-
- #XZ, 09/28/2008: if user select '3', then fetchAllDatabaseData would give us LitCorr in the [1] position
- #XZ, 09/28/2008: if user select '4' or '5', then fetchAllDatabaseData would give us Tissue Corr in the [1] position
- #XZ, 09/28/2008: and Tissue Corr P Value in the [2] position
- if input_trait_GeneId and self.db.type == "ProbeSet" and self.method in ["3", "4", "5"]:
- for i, item in enumerate(allcorrelations):
- if self.method == "3":
- item.append( traitdatabase[1] )
- if self.method == "4" or self.method == "5":
- item.append( traitdatabase[1] )
- item.append( traitdatabase[2] )
-
-
- return totalTraits, allcorrelations
-
-
- def getTableHeaderForPublish(self, method=None, worksheet=None, newrow=None, headingStyle=None):
-
- tblobj_header = []
-
- if method in ["1", "3", "4"]:
- tblobj_header = [[THCell(HT.TD('', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), sort=0),
- THCell(HT.TD('Record', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="id", idx=1),
- THCell(HT.TD('Phenotype', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="pheno", idx=2),
- THCell(HT.TD('Authors', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="auth", idx=3),
- THCell(HT.TD('Year', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="year", idx=4),
- THCell(HT.TD('N', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="nstr", idx=5),
- THCell(HT.TD('Partial r ', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="partial_corr", idx=6),
- THCell(HT.TD('p(partial r)', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text="partial_pv", idx=7),
- THCell(HT.TD('r ', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="corr", idx=8),
- THCell(HT.TD('p(r)', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text="pv", idx=9),
- THCell(HT.TD('delta r', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="delta_corr", idx=10)]]
-
- for ncol, item in enumerate(["Record", "Phenotype", "Authors", "Year", "PubMedID", "N", "Partial r", "p(partial r)", "r ", "p(r)", "delta r"]):
- worksheet.write([newrow, ncol], item, headingStyle)
- worksheet.set_column([ncol, ncol], 2*len(item))
- else:
- tblobj_header = [[THCell(HT.TD('', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), sort=0),
- THCell(HT.TD('Record', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="id", idx=1),
- THCell(HT.TD('Phenotype', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="pheno", idx=2),
- THCell(HT.TD('Authors', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="auth", idx=3),
- THCell(HT.TD('Year', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="year", idx=4),
- THCell(HT.TD('N', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="nstr", idx=5),
- THCell(HT.TD('Partial rho ', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="partial_corr", idx=6),
- THCell(HT.TD('p(partial rho)', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text="partial_pv", idx=7),
- THCell(HT.TD('rho ', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="corr", idx=8),
- THCell(HT.TD('p(rho)', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text="pv", idx=9),
- THCell(HT.TD('delta rho', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="delta_corr", idx=10)]]
-
- for ncol, item in enumerate(["Record", "Phenotype", "Authors", "Year", "PubMedID", "N", "Partial rho", "p(partial rho)", "rho ", "p(rho)", "delta rho"]):
- worksheet.write([newrow, ncol], item, headingStyle)
- worksheet.set_column([ncol, ncol], 2*len(item))
-
- return tblobj_header, worksheet
-
-
- def getTableBodyForPublish(self, traitList, formName=None, worksheet=None, newrow=None, corrScript=None):
-
- tblobj_body = []
-
- for thisTrait in traitList:
- tr = []
-
- trId = str(thisTrait)
-
- #partial corr value could be string 'NA'
- try:
- corrScript.append('corrArray["%s"] = {corr:%1.4f};' % (trId, thisTrait.partial_corr))
- except:
- corrScript.append('corrArray["%s"] = {corr:"NA"};' % (trId))
-
- tr.append(TDCell(HT.TD(HT.Input(type="checkbox", Class="checkbox", name="searchResult",value=trId, onClick="highlight(this)"), nowrap="on", Class="fs12 fwn ffl b1 c222"), text=trId))
-
- tr.append(TDCell(HT.TD(HT.Href(text=thisTrait.name,url="javascript:showTrait('%s', '%s')" % (formName, thisTrait.name), Class="fs12 fwn"), nowrap="yes",align="center", Class="fs12 fwn b1 c222"),str(thisTrait.name), thisTrait.name))
-
- PhenotypeString = thisTrait.post_publication_description
- if thisTrait.confidential:
- if not webqtlUtil.hasAccessToConfidentialPhenotypeTrait(privilege=self.privilege, userName=self.userName, authorized_users=thisTrait.authorized_users):
- PhenotypeString = thisTrait.pre_publication_description
- tr.append(TDCell(HT.TD(PhenotypeString, Class="fs12 fwn b1 c222"), PhenotypeString, PhenotypeString.upper()))
-
- tr.append(TDCell(HT.TD(thisTrait.authors, Class="fs12 fwn b1 c222 fsI"),thisTrait.authors, thisTrait.authors.strip().upper()))
-
- try:
- PubMedLinkText = myear = repr = int(thisTrait.year)
- except:
- PubMedLinkText = repr = "N/A"
- myear = 0
- if thisTrait.pubmed_id:
- PubMedLink = HT.Href(text= repr,url= webqtlConfig.PUBMEDLINK_URL % thisTrait.pubmed_id,target='_blank', Class="fs12 fwn")
- else:
- PubMedLink = repr
-
- tr.append(TDCell(HT.TD(PubMedLink, Class="fs12 fwn b1 c222", align='center'), repr, myear))
-
- repr = '%d' % thisTrait.NOverlap
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.NOverlap))
-
- try:
- repr = '%3.3f' % thisTrait.partial_corr
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn b1 c222", align='right', nowrap="on"), repr, abs(thisTrait.partial_corr)))
- except:
- repr = 'NA'
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222", align='left'), text=repr, val=0 ))
-
- repr = webqtlUtil.SciFloat(thisTrait.partial_corrPValue)
- tr.append(TDCell(HT.TD(repr,nowrap='ON', Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.partial_corrPValue))
-
- repr = '%3.3f' % thisTrait.corr
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn b1 c222", align='right', nowrap="on"), repr, abs(thisTrait.corr)))
-
- repr = webqtlUtil.SciFloat(thisTrait.corrPValue)
- tr.append(TDCell(HT.TD(repr,nowrap='ON', Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.corrPValue))
-
- #delta
- try:
- delta = '%3.3f' % ( float(thisTrait.partial_corr) - float(thisTrait.corr) )
- tr.append(TDCell(HT.TD(delta, Class="fs12 fwn ffl b1 c222", align='right', nowrap="on"), text=delta, val=abs(float(delta)) ))
- except:
- delta = 'NA'
- tr.append(TDCell(HT.TD(delta, Class="fs12 fwn ffl b1 c222", align='left'), text=delta, val=0 ))
-
- tblobj_body.append(tr)
-
- for ncol, item in enumerate([thisTrait.name, PhenotypeString, thisTrait.authors, thisTrait.year, thisTrait.pubmed_id, thisTrait.NOverlap, thisTrait.partial_corr, thisTrait.partial_corrPValue, thisTrait.corr, thisTrait.corrPValue, delta]):
- worksheet.write([newrow, ncol], str(item) )
- newrow += 1
-
- return tblobj_body, worksheet, corrScript
-
-
- def getTableHeaderForGeno(self, method=None, worksheet=None, newrow=None, headingStyle=None):
- tblobj_header = []
-
- if method in ["1", "3", "4"]:
- tblobj_header = [[THCell(HT.TD('', Class="fs13 fwb ffl b1 cw cbrb"), sort=0),
- THCell(HT.TD('Locus', Class="fs13 fwb ffl b1 cw cbrb",align='center'), text='locus', idx=1),
- THCell(HT.TD('Chr', Class="fs13 fwb ffl b1 cw cbrb"), text='chr', idx=2),
- THCell(HT.TD('Megabase', Class="fs13 fwb ffl b1 cw cbrb"), text='Mb', idx=3),
- THCell(HT.TD('N', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text='nstr', idx=4),
- THCell(HT.TD('Partial r ', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text='partial_corr', idx=5),
- THCell(HT.TD('p(partial r)', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text='partial_pv', idx=6),
- THCell(HT.TD('r ', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text='corr', idx=7),
- THCell(HT.TD('p(r)', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text='pv', idx=8),
- THCell(HT.TD('delta r', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text='delta_corr', idx=9)]]
-
- for ncol, item in enumerate(['Locus', 'Chr', ' Mb ', ' N ', 'Partial r', 'p(partial r)', 'r ', 'p(r)', 'delta r' ]):
- worksheet.write([newrow, ncol], item, headingStyle)
- worksheet.set_column([ncol, ncol], 2*len(item))
- else:
- tblobj_header = [[THCell(HT.TD('', Class="fs13 fwb ffl b1 cw cbrb"), sort=0),
- THCell(HT.TD('Locus', Class="fs13 fwb ffl b1 cw cbrb",align='center'), text='locus', idx=1),
- THCell(HT.TD('Chr', Class="fs13 fwb ffl b1 cw cbrb"), text='chr', idx=2),
- THCell(HT.TD('Megabase', Class="fs13 fwb ffl b1 cw cbrb"), text='Mb', idx=3),
- THCell(HT.TD('N', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text='nstr', idx=4),
- THCell(HT.TD('Partial rho', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text='partial_corr', idx=5),
- THCell(HT.TD('p(partial rho)', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text='partial_pv', idx=6),
- THCell(HT.TD('rho ', Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text='corr', idx=7),
- THCell(HT.TD('p(rho)', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text='pv', idx=8),
- THCell(HT.TD('delta rho', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text='delta_corr', idx=9)]]
-
- for ncol, item in enumerate(['Locus', 'Chr', ' Mb ', ' N ', 'Partial rho', 'p(partial rho)', 'rho ', 'p(rho)', 'delta rho' ]):
- worksheet.write([newrow, ncol], item, headingStyle)
- worksheet.set_column([ncol, ncol], 2*len(item))
-
- return tblobj_header, worksheet
-
-
-
- def getTableBodyForGeno(self, traitList, formName=None, worksheet=None, newrow=None, corrScript=None):
-
- tblobj_body = []
-
- for thisTrait in traitList:
- tr = []
-
- trId = str(thisTrait)
-
- #partial corr value could be string 'NA'
- try:
- corrScript.append('corrArray["%s"] = {corr:%1.4f};' % (trId, thisTrait.partial_corr))
- except:
- corrScript.append('corrArray["%s"] = {corr:"NA"};' % (trId))
-
- tr.append(TDCell(HT.TD(HT.Input(type="checkbox", Class="checkbox", name="searchResult",value=trId, onClick="highlight(this)"), nowrap="on", Class="fs12 fwn ffl b1 c222"), text=trId))
-
- tr.append(TDCell(HT.TD(HT.Href(text=thisTrait.name,url="javascript:showTrait('%s', '%s')" % (formName, thisTrait.name), Class="fs12 fwn ffl"),align="center", Class="fs12 fwn ffl b1 c222"), text=thisTrait.name, val=thisTrait.name.upper()))
-
- #tr.append(TDCell(HT.TD(thisTrait.chr, Class="fs12 fwn ffl b1 c222", align='right'), text=str(thisTrait.chr)))
-
- try:
- Mbvalue = int(thisTrait.chr)*1000 + thisTrait.mb
- except:
- if not thisTrait.chr or not thisTrait.mb:
- Mbvalue = 1000000
- elif thisTrait.chr.upper() == 'X':
- Mbvalue = 20*1000 + thisTrait.mb
- else:
- Mbvalue = ord(str(thisTrait.chr).upper()[0])*1000 + thisTrait.mb
-
- tr.append(TDCell( HT.TD(thisTrait.chr, Class="fs12 fwn b1 c222", align='right'), thisTrait.chr, Mbvalue) )
- tr.append(TDCell(HT.TD(thisTrait.mb, Class="fs12 fwn ffl b1 c222", align='right'), text=str(thisTrait.mb), val=Mbvalue))
-
- repr = '%d' % thisTrait.NOverlap
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.NOverlap))
-
- try:
- repr='%3.3f' % thisTrait.partial_corr
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222", align='right',nowrap='ON'),repr,abs(thisTrait.partial_corr)))
- except:
- repr = 'NA'
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222", align='left'), text=repr, val=0 ))
-
- repr = webqtlUtil.SciFloat(thisTrait.partial_corrPValue)
- tr.append(TDCell(HT.TD(repr,nowrap='ON', Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.partial_corrPValue))
-
- repr = '%3.3f' % thisTrait.corr
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn b1 c222", align='right',nowrap='ON'), repr, abs(thisTrait.corr)))
-
- repr = webqtlUtil.SciFloat(thisTrait.corrPValue)
- tr.append(TDCell(HT.TD(repr,nowrap='ON', Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.corrPValue))
-
- #delta
- try:
- delta = '%3.3f' % ( float(thisTrait.partial_corr) - float(thisTrait.corr) )
- tr.append(TDCell(HT.TD(delta, Class="fs12 fwn ffl b1 c222", align='right', nowrap='ON'), text=delta, val=abs(float(delta)) ))
- except:
- delta = 'NA'
- tr.append(TDCell(HT.TD(delta, Class="fs12 fwn ffl b1 c222", align='left'), text=delta, val=0 ))
-
- tblobj_body.append(tr)
-
- for ncol, item in enumerate([thisTrait.name, thisTrait.chr, thisTrait.mb, thisTrait.NOverlap, thisTrait.partial_corr, thisTrait.partial_corrPValue, thisTrait.corr, thisTrait.corrPValue, delta]):
- worksheet.write([newrow, ncol], item)
- newrow += 1
-
- return tblobj_body, worksheet, corrScript
-
-
- def getTableHeaderForProbeSet(self, method=None, worksheet=None, newrow=None, headingStyle=None):
-
- tblobj_header = []
-
- if method in ["1","3","4"]:
- tblobj_header = [[THCell(HT.TD(' ', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), sort=0),
- THCell(HT.TD('Record',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="id", idx=1),
- THCell(HT.TD('','Symbol',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="symbol", idx=2),
- THCell(HT.TD('','Description',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="desc", idx=3),
- #XZ, 12/09/2008: sort chr
- THCell(HT.TD('','Chr',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="chr", idx=4),
- THCell(HT.TD('','Mb',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Mb", idx=5),
- THCell(HT.TD('Mean',HT.BR(),'Expr',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="mean", idx=6),
- THCell(HT.TD('N',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text="nstr", idx=7),
- THCell(HT.TD(HT.Href(
- text = HT.Span('Sample',HT.BR(), 'Partial r', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#genetic_r"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="partial_corr", idx=8),
- THCell(HT.TD(HT.Href(
- text = HT.Span('Sample',HT.BR(), 'p(partial r)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#genetic_p_r"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="partial_pv", idx=9),
- THCell(HT.TD(HT.Href(
- text = HT.Span('Sample',HT.BR(), 'r', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#genetic_r"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="corr", idx=10),
- THCell(HT.TD(HT.Href(
- text = HT.Span('Sample',HT.BR(), 'p(r)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#genetic_p_r"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="pv", idx=11),
- THCell(HT.TD('delta',HT.BR(), 'r', HT.BR(), Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text="delta_corr", idx=12),
- THCell(HT.TD(HT.Href(
- text = HT.Span('Pubmed',HT.BR(), 'r', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#literatureCorr"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="lcorr", idx=13),
- #XZ, 09/22/2008: tissue correlation
- THCell(HT.TD(HT.Href(
- text = HT.Span('Tissue',HT.BR(), 'r', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#tissue_r"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="tissuecorr", idx=14),
- THCell(HT.TD(HT.Href(
- text = HT.Span('Tissue',HT.BR(), 'p(r)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#tissue_p_r"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="tissuepvalue", idx=15)]]
-
- for ncol, item in enumerate(['Record', 'Gene ID', 'Symbol', 'Description', 'Chr', 'Megabase', 'Mean Expr', 'N ', 'Sample Partial r', 'Sample p(partial r)', 'Sample r', 'Sample p(r)', 'delta r', 'Lit Corr', 'Tissue r', 'Tissue p(r)']):
- worksheet.write([newrow, ncol], item, headingStyle)
- worksheet.set_column([ncol, ncol], 2*len(item))
- else:
- tblobj_header = [[THCell(HT.TD(' ', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), sort=0),
- THCell(HT.TD('Record',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="id", idx=1),
- THCell(HT.TD('','Symbol',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="symbol", idx=2),
- THCell(HT.TD('','Description',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="desc", idx=3),
- THCell(HT.TD('','Chr',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="chr", idx=4),
- THCell(HT.TD('','Mb',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Mb", idx=5),
- THCell(HT.TD('Mean',HT.BR(),'Expr',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="mean", idx=6),
- THCell(HT.TD('N',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text="nstr", idx=7),
- THCell(HT.TD(HT.Href(
- text = HT.Span('Sample',HT.BR(), 'Partial rho', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#genetic_rho"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="partial_corr", idx=8),
- THCell(HT.TD(HT.Href(
- text = HT.Span('Sample',HT.BR(), 'p(partial rho)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#genetic_p_rho"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="partial_pv", idx=9),
- THCell(HT.TD(HT.Href(
- text = HT.Span('Sample',HT.BR(), 'rho', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#genetic_r"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="corr", idx=10),
- THCell(HT.TD(HT.Href(
- text = HT.Span('Sample',HT.BR(), 'p(rho)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#genetic_p_r"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="pv", idx=11),
- THCell(HT.TD('delta',HT.BR(),'rho', HT.BR(), Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), text="delta_corr", idx=12),
- THCell(HT.TD(HT.Href(
- text = HT.Span('Pubmed',HT.BR(), 'r', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#literatureCorr"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="lcorr", idx=13),
- #XZ, 09/22/2008: tissue correlation
- THCell(HT.TD(HT.Href(
- text = HT.Span('Tissue',HT.BR(), 'rho', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#tissue_rho"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="tissuecorr", idx=14),
- THCell(HT.TD(HT.Href(
- text = HT.Span('Tissue',HT.BR(), 'p(rho)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"),
- target = '_blank',
- url = "/correlationAnnotation.html#tissue_p_rho"),
- Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="tissuepvalue", idx=15)]]
-
- for ncol, item in enumerate(['Record', 'Gene ID', 'Symbol', 'Description', 'Chr', 'Megabase', 'Mean Expr', 'N ', 'Sample Partial rho', 'Sample p(partial rho)', 'Sample rho', 'Sample p(rho)', 'delta rho', 'Pubmed r', 'Tissue rho', 'Tissue p(rho)']):
- worksheet.write([newrow, ncol], item, headingStyle)
- worksheet.set_column([ncol, ncol], 2*len(item))
-
- return tblobj_header, worksheet
-
-
- def getTableBodyForProbeSet(self, traitList=[], primaryTrait=None, formName=None, worksheet=None, newrow=None, corrScript=None):
-
- tblobj_body = []
-
- for thisTrait in traitList:
-
- if thisTrait.symbol:
- pass
- else:
- thisTrait.symbol = "N/A"
-
- if thisTrait.geneid:
- symbolurl = HT.Href(text=thisTrait.symbol,target='_blank',url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene&cmd=Retrieve&dopt=Graphics&list_uids=%s" % thisTrait.geneid, Class="fs12 fwn")
- else:
- symbolurl = HT.Href(text=thisTrait.symbol,target='_blank',url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?CMD=search&DB=gene&term=%s" % thisTrait.symbol, Class="fs12 fwn")
-
- tr = []
-
- trId = str(thisTrait)
-
- #partial corr value could be string 'NA'
- try:
- corrScript.append('corrArray["%s"] = {corr:%1.4f};' % (trId, thisTrait.partial_corr))
- except:
- corrScript.append('corrArray["%s"] = {corr:"NA"};' % (trId))
-
- #XZ, 12/08/2008: checkbox
- tr.append(TDCell(HT.TD(HT.Input(type="checkbox", Class="checkbox", name="searchResult",value=trId, onClick="highlight(this)"), nowrap="on", Class="fs12 fwn ffl b1 c222"), text=trId))
-
- #XZ, 12/08/2008: probeset name
- tr.append(TDCell(HT.TD(HT.Href(text=thisTrait.name,url="javascript:showTrait('%s', '%s')" % (formName,thisTrait.name), Class="fs12 fwn"), Class="fs12 fwn b1 c222"), thisTrait.name, thisTrait.name.upper()))
-
- #XZ, 12/08/2008: gene symbol
- tr.append(TDCell(HT.TD(symbolurl, Class="fs12 fwn b1 c222 fsI"),thisTrait.symbol, thisTrait.symbol.upper()))
-
- #XZ, 12/08/2008: description
- #XZ, 06/05/2009: Rob asked to add probe target description
- description_string = str(thisTrait.description).strip()
- target_string = str(thisTrait.probe_target_description).strip()
-
- description_display = ''
-
- if len(description_string) > 1 and description_string != 'None':
- description_display = description_string
- else:
- description_display = thisTrait.symbol
-
- if len(description_display) > 1 and description_display != 'N/A' and len(target_string) > 1 and target_string != 'None':
- description_display = description_display + '; ' + target_string.strip()
-
- tr.append(TDCell(HT.TD(description_display, Class="fs12 fwn b1 c222"), description_display, description_display))
-
- #XZ, 12/08/2008: Mbvalue is used for sorting
- try:
- Mbvalue = int(thisTrait.chr)*1000 + thisTrait.mb
- except:
- if not thisTrait.chr or not thisTrait.mb:
- Mbvalue = 1000000
- elif thisTrait.chr.upper() == 'X':
- Mbvalue = 20*1000 + thisTrait.mb
- else:
- Mbvalue = ord(str(thisTrait.chr).upper()[0])*1000 + thisTrait.mb
-
- #XZ, 12/08/2008: chromosome number
- #XZ, 12/10/2008: use Mbvalue to sort chromosome
- tr.append(TDCell( HT.TD(thisTrait.chr, Class="fs12 fwn b1 c222", align='right'), thisTrait.chr, Mbvalue) )
-
- #XZ, 12/08/2008: Rob wants 6 digit precision, and we have to deal with that the mb could be None
- if not thisTrait.mb:
- tr.append(TDCell(HT.TD(thisTrait.mb, Class="fs12 fwn b1 c222",align='right'), thisTrait.mb, Mbvalue))
- else:
- tr.append(TDCell(HT.TD('%.6f' % thisTrait.mb, Class="fs12 fwn b1 c222", align='right'), thisTrait.mb, Mbvalue))
-
- #XZ, 01/12/08: This SQL query is much faster.
- self.cursor.execute("""
- select ProbeSetXRef.mean from ProbeSetXRef, ProbeSet
- where ProbeSetXRef.ProbeSetFreezeId = %d and
- ProbeSet.Id = ProbeSetXRef.ProbeSetId and
- ProbeSet.Name = '%s'
- """ % (thisTrait.db.id, thisTrait.name))
- result = self.cursor.fetchone()
- if result:
- if result[0]:
- mean = result[0]
- else:
- mean=0
- else:
- mean = 0
-
- #XZ, 06/05/2009: It is neccessary to turn on nowrap
- repr = "%2.3f" % mean
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222", align='right', nowrap='ON'),repr, mean))
-
- #XZ: number of overlaped cases for partial corr
- repr = '%d' % thisTrait.NOverlap
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.NOverlap))
-
- #XZ: sample partial correlation
- try:
- repr='%3.3f' % thisTrait.partial_corr
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222", align='right', nowrap='ON'),repr,abs(thisTrait.partial_corr)))
- except:
- repr = 'NA'
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222", align='left'), text=repr, val=0 ))
-
- #XZ: p value of genetic partial correlation
- repr = webqtlUtil.SciFloat(thisTrait.partial_corrPValue)
- tr.append(TDCell(HT.TD(repr,nowrap='ON', Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.partial_corrPValue))
-
- repr = '%3.3f' % thisTrait.corr
- tr.append(TDCell(HT.TD(repr, Class="fs12 fwn b1 c222", align='right',nowrap='ON'), repr, abs(thisTrait.corr)))
-
- repr = webqtlUtil.SciFloat(thisTrait.corrPValue)
- tr.append(TDCell(HT.TD(repr,nowrap='ON', Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.corrPValue))
-
- #delta
- try:
- delta = '%3.3f' % ( float(thisTrait.partial_corr) - float(thisTrait.corr) )
- tr.append(TDCell(HT.TD(delta, Class="fs12 fwn ffl b1 c222", align='right', nowrap='ON'), text=delta, val=abs(float(delta)) ))
- except:
- delta = 'NA'
- tr.append(TDCell(HT.TD(delta, Class="fs12 fwn ffl b1 c222", align='left'), text=delta, val=0 ))
-
- #XZ, 12/08/2008: literature correlation
- LCorr = 0.0
- LCorrStr = "N/A"
- if hasattr(thisTrait, 'LCorr') and thisTrait.LCorr:
- LCorr = thisTrait.LCorr
- LCorrStr = "%2.3f" % thisTrait.LCorr
- tr.append(TDCell(HT.TD(LCorrStr, Class="fs12 fwn b1 c222", align='right'), LCorrStr, abs(LCorr)))
-
- #XZ, 09/22/2008: tissue correlation.
- TCorr = 0.0
- TCorrStr = "N/A"
- #XZ, 11/18/2010: need to pass two gene symbols
- if hasattr(thisTrait, 'tissueCorr') and thisTrait.tissueCorr:
- TCorr = thisTrait.tissueCorr
- TCorrStr = "%2.3f" % thisTrait.tissueCorr
- #NL, 07/19/2010: add a new parameter rankOrder for js function 'showTissueCorrPlot'
- rankOrder =thisTrait.rankOrder
- TCorrPlotURL = "javascript:showTissueCorrPlot('%s','%s','%s',%d)" %(formName, primaryTrait.symbol, thisTrait.symbol,rankOrder)
- tr.append(TDCell(HT.TD(HT.Href(text=TCorrStr, url=TCorrPlotURL, Class="fs12 fwn ff1"), Class="fs12 fwn ff1 b1 c222", align='right'), TCorrStr, abs(TCorr) ))
- else:
- tr.append(TDCell(HT.TD(TCorrStr, Class="fs12 fwn b1 c222", align='right'), TCorrStr, abs(TCorr)))
-
- #XZ, 12/08/2008: p value of tissue correlation
- TPValue = 1.0
- TPValueStr = "N/A"
- if hasattr(thisTrait, 'tissueCorr') and thisTrait.tissueCorr: #XZ, 09/22/2008: thisTrait.tissuePValue can't be used here because it could be 0
- TPValue = thisTrait.tissuePValue
- TPValueStr = "%2.3f" % thisTrait.tissuePValue
- tr.append(TDCell(HT.TD(TPValueStr, Class="fs12 fwn b1 c222", align='right'), TPValueStr, abs(TPValue) ))
-
- tblobj_body.append(tr)
-
- for ncol, item in enumerate([thisTrait.name, thisTrait.geneid, thisTrait.symbol, thisTrait.description, thisTrait.chr, thisTrait.mb, mean, thisTrait.NOverlap, thisTrait.partial_corr, thisTrait.partial_corrPValue, thisTrait.corr, thisTrait.corrPValue, delta, LCorrStr, TCorrStr, TPValueStr]):
- worksheet.write([newrow, ncol], item)
-
- newrow += 1
-
- return tblobj_body, worksheet, corrScript
-
-
- def getFormForPrimaryAndControlTraits (self, primaryTrait, controlTraits):
-
- info_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', 'database':'_', 'ProbeSetID':'_', 'CellID':'_' }#XZ: These four parameters are required by javascript function showDatabase2.
-
- for key in hddn.keys():
- info_form.append(HT.Input(name=key, value=hddn[key], type='hidden'))
-
- info_form.append(HT.Paragraph("Primary Trait", Class="subtitle"), '\n')
-
- primaryTraitTable = HT.TableLite(cellSpacing=4,cellPadding=0,width="90%",border=0)
- descriptionString = primaryTrait.genHTML(dispFromDatabase=1)
- if primaryTrait.db.type == 'Publish' and primaryTrait.confidential:
- descriptionString = primaryTrait.genHTML(dispFromDatabase=1, privilege=self.privilege, userName=self.userName, authorized_users=primaryTrait.authorized_users)
- primaryTraitTable.append(HT.TR(HT.TD(HT.Href(text='%s' % descriptionString, url="javascript:showDatabase2('%s','%s','%s')" % (primaryTrait.db.name,primaryTrait.name,primaryTrait.cellid), Class="fs12 fwn") )))
-
- info_form.append(primaryTraitTable)
-
- info_form.append(HT.Paragraph("Control Traits", Class="subtitle"), '\n')
-
- controlTraitsTable = HT.TableLite(cellSpacing=4,cellPadding=0,width="90%",border=0)
-
- seq = 1
-
- ## Generate the listing table for control traits
- for thisTrait in controlTraits:
- descriptionString = thisTrait.genHTML(dispFromDatabase=1)
- if thisTrait.db.type == 'Publish' and thisTrait.confidential:
- descriptionString = thisTrait.genHTML(dispFromDatabase=1, privilege=self.privilege, userName=self.userName, authorized_users=thisTrait.authorized_users)
- controlTraitsTable.append(HT.TR(HT.TD("%d."%seq,align="right",width=10),
- HT.TD(HT.Href(text='%s' % descriptionString,url="javascript:showDatabase2('%s','%s','%s')" % (thisTrait.db.name,thisTrait.name,thisTrait.cellid), Class="fs12 fwn") )))
- seq += 1
-
- info_form.append(controlTraitsTable)
-
- return info_form
generated by cgit v1.2.3 (git 2.44.0) at 2024-10-19 23:44:27 +0000