# 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 # FUTURE PLANS: # 1. Make the search species independent. Right now, it is fairly hard-coded to work with mouse only. Although it would not be too much trouble to add another species, at the time of writing, we have no # variant data for anything except mice, so spending time fixing the code with respect to species independence is unnecessary. However, if you expand on the code, you should keep this in mind. # 2. There needs to be some way to display mutliple strains in the InDel browser. # 3. We need CNV and Transposon data. This should mostly come from Xusheng, at least for B vs. D, and it should be included in the Variants browser, which may have to either be restructured, or # maybe just have columns added to it (if we're lucky). #Code for the Variant Browser module. It's somewhat commented. from mod_python import Cookie from htmlgen import HTMLgen2 as HT import string import os import piddle as pid import time import pyXLWriter as xl from types import ListType import re import cPickle #import snpBrowserUtils from base import webqtlConfig from base.GeneralObject import GeneralObject from utility import Plot from base.templatePage import templatePage #from GeneListAnnot import GeneListAnnot from utility import webqtlUtil from utility.THCell import THCell from utility.TDCell import TDCell #################################################################### ## SNP Browser ## Prints information about every SNP that lies in a specified range #################################################################### #get current file path current_file_name = __file__ pathname = os.path.dirname( current_file_name ) abs_path = os.path.abspath(pathname) class snpBrowserPage(templatePage): MAXSNPRETURN = 5000 # This can take an awful long time to load. If there are more than 5000 SNPs, then it loads the SNP density graph instead (which is much faster, but doesn't show the exact data). MAXMB = 50 # Clips the graph to (Start Mb through Start+50 Mb) if someone searches for a larger region than that _scriptfile = "main.py?FormID=SnpBrowserResultPage" def __init__(self, fd): templatePage.__init__(self,fd) if not self.openMysql(): return self.remote_ip = fd.remote_ip self.formdata = fd.formdata # This is for passing the VARIANT TYPE to the table creation process self.snp_list = None submitStatus = self.formdata.getfirst("submitStatus", "") opt = GeneralObject() self.initializeDisplayParameters(fd,opt) info_line="" snpTable="" if submitStatus: # For SnpBrowser result page opt.xls = 1 try: # for sortable columns, need to build dict for genTableObj function tblobj = {} filename= webqtlUtil.genRandStr("snpBrowser_") snpMatches, tblobj = self.genSnpTable(opt) if snpMatches >0 and snpMatches <=self.MAXSNPRETURN: # creat object for result table for sort function objfile = open('%s.obj' % (webqtlConfig.TMPDIR+filename), 'wb') cPickle.dump(tblobj, objfile) objfile.close() sortby = ("Index", "down") snpTable = HT.Div(webqtlUtil.genTableObj(tblobj=tblobj, file=filename, sortby=sortby, tableID = "sortable", addIndex = "1"), Id="sortable") else: #updated by NL 07-11-2011: density map can not be cPickled snpTable=tblobj # This writes the info at top above the search criteria. strainText = " - among all available strains in the group" info_line = HT.Paragraph("%d %s(s) on Chr %s: %0.6f - %0.6f (Mb, mm9" % (snpMatches, opt.variant,opt.chromosome, opt.startMb, opt.endMb), Class="fs14 fwb ffl black") if self.snp_list: info_line.contents[0]+= ", SNP: %s)" % opt.geneName elif opt.geneName: info_line.contents[0]+= ", Gene: %s)" % opt.geneName else: info_line.contents[0]+= ")" except: heading = "Variant Browser" detail = ["No gene or %s record was found that matches %s." % (opt.variant,opt.geneName)] self.error(heading=heading,detail=detail) return else: opt.use_custom = True opt.diffAlleles=True # SnpBrowser default display part info_link = HT.Input(type="button", value="Info", Class="button", onClick="javascript:openNewWin('/snpbrowser.html');") if opt.xslFilename: xlsDownloadButton= HT.Input(type="button", name="submitStatus",value=" Download Table ",onClick= "location.href='/tmp/%s'" % opt.xslFilename, Class='button') title = HT.Paragraph("Variant Browser ", info_link, "  ",xlsDownloadButton, Class="title") else: title = HT.Paragraph("Variant Browser ", info_link, Class="title") newPaddingForm = self.genBrowserForm(opt) descriptionTable = HT.TableLite(border=0, cellpadding=0, cellspacing=0) descriptionTable.append(HT.TR(HT.TD(info_line, colspan=3)), HT.TR(HT.TD("", height="20", colspan=3)), HT.TR(HT.TD(newPaddingForm,Class="doubleBorder", valign="top", colspan=3)), HT.TR(HT.TD("", height="20", colspan=3)), HT.TR(HT.TD(snpTable, colspan=3))) self.dict['body'] = HT.TD(title, HT.Blockquote(descriptionTable, HT.P()),valign="top",height="200", width="100%") self.dict['title'] = "Variant Browser" pass ################################################################ # Initializes all of the snpBrowserPage class parameters, # acquiring most values from the formdata (fd) ################################################################ def initializeDisplayParameters(self, fd,opt): # COLUMN 1: items in paddingTab1 opt.variant = self.formdata.getfirst("variant","SNP") opt.geneName = string.strip(self.formdata.getfirst("geneName", "")) opt.chromosome = self.formdata.getfirst("chr", "19") startMb, endMb =self.initialMb() opt.startMb = startMb opt.endMb = endMb # COLUMN 2: items in paddingTab2 opt.allStrainNamesPair = self.getStrainNamePair() opt.allStrainNameList=[v[0] for v in opt.allStrainNamesPair] opt.customStrain = self.formdata.getfirst("customStrain",None) if opt.customStrain: opt.use_custom = True else: opt.use_custom = False chosenStrains = self.formdata.getfirst("chosenStrains") strainList=[] # chosen strain selectbox incudes all strains that will be displayed in the search results if the "Limit to" checkbox is checked. # by default, chosen strain selectbox includes 9 strains. # All strains in chosen strain selectbox will be saved into cookie after clicking 'Search' button. # chosen strain selectbox is set as single choice. # The original chosenStrains parameter is string type (chosenStrains = self.formdata.getfirst("chosenStrains")), # then we split it into list if it is not empty ( chosenStrains = list(string.split(chosenStrains,',')) ) # Case 1, no item is in selected status in chosen strain selectbox. chosenStrains is None. No converting to list. # Case 2, user might have added one strain into chosen strain selectbox or clicked one item in chosen strain selectbox. # After converting to list type, the chosenStrains list has one item. # Case 3, other classes might have called snpBrowserPage, such as from ProbeInfoPage,the strains will be passed via 'chosenStrains' parameter. # After converting to list type, the chosenStrains list has two items. # In case 1 and 2, we will get the chosen strains from cookie or by using default value of 'chosenStrains'. opt.chosenStrains = self.retrieveCustomStrains(fd) # in case 3, get strain names from 'chosenStrains' parameter if chosenStrains: if (not (type(chosenStrains) is ListType)): chosenStrains = list(string.split(chosenStrains,',')) if len(chosenStrains)>1 : for item in chosenStrains: strainList.append((item,item)) opt.chosenStrains=strainList opt.diffAlleles =self.formdata.getfirst("diffAlleles", None) if opt.diffAlleles: opt.diffAlleles = True else: opt.diffAlleles = False # COLUMN 3: items in paddingTab3 opt.domain = self.formdata.getfirst("domain") if opt.domain == None or len(opt.domain) == 0: opt.domain = [""] elif not type(opt.domain) is ListType: opt.domain = [opt.domain] opt.function = self.formdata.getfirst("exonfunction") if opt.function == None or len(opt.function) == 0: opt.function = [""] elif not type(opt.function) is ListType: opt.function = [opt.function] opt.chosenSource=self.getSource() opt.source = self.formdata.getfirst("source") if opt.source == None or len(opt.source) == 0: opt.source = [""] elif not type(opt.source) is ListType: opt.source = [opt.source] opt.conservationCriteria = self.formdata.getfirst("criteria",">=") opt.score = self.formdata.getfirst("score","0.0") opt.redundant = self.formdata.getfirst("redundant", None) if opt.redundant: opt.redundant_checked = True else: opt.redundant_checked = False # initial xsl file name opt.xslFilename="" opt.alleleValueList=[] # SnpBrowser page top part def genBrowserForm(self, opt): # COLUMN 1: items in paddingTab1 variantSelect = HT.Select(name="variant", Class="typeDropdownWidth",data=[("SNP", "SNP"), ("InDel", "InDel")], selected=[opt.variant]) geneBox = HT.Input(type="text", Class="typeDropdownWidth",name="geneName", value=opt.geneName, size="12") selectChrBox = HT.Select(name="chr",Class="typeDropdownWidth", data=[(1,'1'), (2,'2'), (3,'3'), (4,'4'), (5,'5'), (6,'6'), (7,'7'), (8,'8'), (9,'9'), (10,'10'), (11,'11'), (12,'12'), (13,'13'), (14,'14'), (15,'15'), (16,'16'), (17,'17'), (18,'18'), (19,'19'), ('X', 'X')], selected=[opt.chromosome], onChange = "Javascript:this.form.geneName.value=''") mbStartBox = HT.Input(type="text", Class="typeDropdownWidth",name="start", size="10", value=opt.startMb, onChange = "Javascript:this.form.geneName.value=''") mbEndBox = HT.Input(type="text", Class="typeDropdownWidth",name="end", value=opt.endMb, size="10", onChange = "Javascript:this.form.geneName.value=''") submitButton = HT.Input(type="submit", name="submitStatus",value=" Search ", Class="button") # COLUMN 2: items in paddingTab2 div4 = HT.Div(Id='menu_s3') strainBox3 = HT.Select(name="s3", data=opt.allStrainNamesPair, Class="customBoxWidth") div4.append(strainBox3) addStrainButton = HT.Input(type="button", value="Add", Class="button", onClick="addToList(this.form.s3.options[this.form.s3.selectedIndex].text, this.form.s3.options[this.form.s3.selectedIndex].value, this.form.chosenStrains); this.form.chosenStrains.selectedIndex++") customStrainBox = HT.Input(type="checkbox", name="customStrain", checked=opt.use_custom, size="100") customStrainSelect = HT.Select(name="chosenStrains",data=opt.chosenStrains, multiple=False, Class="customBoxWidth", size=11) removeStrainButton = HT.Input(type="button", value=" Cut ", Class="button", onClick="removeFromList(this.form.chosenStrains.selectedIndex, this.form.chosenStrains)") diffAlleles = HT.Input(type="checkbox", name="diffAlleles", checked=opt.diffAlleles) # COLUMN 3: items in paddingTab3 domainBox = HT.Select(name="domain", Class="domainDropdownWidth",data=[("All", ""),("Exon","Exon"),("     5' UTR","5' UTR"), ("     Coding Region","Coding"),("     3' UTR","3' UTR"), ("Intron", "Intron"), ("     Splice Site", "Splice Site"),("     Nonsplice Site", "Nonsplice Site"), ("Upstream","Upstream"),("Downstream","Downstream"), ("Intergenic","Intergenic")], selected=opt.domain, multiple=True,size=4,onChange = "Javascript:snpbrowser_function_refresh()") functionBox = HT.Select(name="exonfunction", data=[("All", ""),("Nonsynonymous","Nonsynonymous"),("Synonymous","Synonymous"),("Start Gained", "Start Gained"),("Start Lost", "Start Lost"),("Stop Gained", "Stop Gained"),("Stop Lost", "Stop Lost")], selected=opt.function,multiple=True, size=3, Class="domainDropdownWidth", onChange="Javascript:snpbrowser_domain_refresh()") filterBox = HT.Select(name="criteria", data=[(">=", ">="), ("=", "=="), ("<=","<=")], selected=[opt.conservationCriteria]) sourceBox = HT.Select(name="source", data=opt.chosenSource, selected=opt.source,Class="domainDropdownWidth") scoreBox = HT.Input(type="text", name="score", value=opt.score, size="5") redundantBox = HT.Input(type="checkbox", name="redundant", checked=opt.redundant_checked) # This is where the actual table is structured, and it displays the variables initialized above paddingTable = HT.TableLite(border=0) paddingTab1 = HT.TableLite(border=0) paddingTab2 = HT.TableLite(border=0) paddingTab3 = HT.TableLite(border=0) # COLUMN 1 paddingTab1.append( HT.TR(HT.TD("Type :", Class="fwb", align="right", NOWRAP=1), HT.TD(variantSelect, NOWRAP=1)), HT.TR(HT.TD("Gene or ID :", Class="fwb", align="right", NOWRAP=1),HT.TD(geneBox, NOWRAP=1)), HT.TR(HT.TD("                      Or select", Class="fwb cr", colspan=3, align="LEFT")), HT.TR(HT.TD("Chr :", Class="fwb", align="right", NOWRAP=1), HT.TD(selectChrBox, NOWRAP=1)),HT.TR(HT.TD("Mb :", Class="fwb", align="right", NOWRAP=1), HT.TD(mbStartBox)), HT.TR(HT.TD(HT.Font("                    to", size=-1,),HT.TD(mbEndBox, NOWRAP=1))), HT.TR(HT.TD(HT.HR(width="99%"), colspan=3, height=10)), HT.TR(HT.TD(HT.TD(submitButton, NOWRAP=1))) ) # COLUMN 2 paddingTab2.append( HT.TR(HT.TD("Strains:", Class="fwb", align="right", NOWRAP=1), HT.TD(width=10),HT.TD(div4),HT.TD(addStrainButton)), HT.TR(HT.TD("Limit to:", customStrainBox, Class="fwb cr", align="right", NOWRAP=1),HT.TD(width=0),HT.TD(customStrainSelect),HT.TD(removeStrainButton)) ) # COLUMN 3 paddingTab3.append( HT.TR(HT.TD("Domain:", Class="fwb", align="right", NOWRAP=1), HT.TD(width=10), HT.TD(domainBox, NOWRAP=1)), HT.TR(HT.TD("Function:", Class="fwb", align="right", NOWRAP=1), HT.TD(width=10), HT.TD(functionBox, NOWRAP=1)), HT.TR(HT.TD("Source:", Class="fwb", align="right", NOWRAP=1), HT.TD(width=4), HT.TD(sourceBox, NOWRAP=1)), HT.TR(HT.TD("ConScore:", Class="fwb", align="right", NOWRAP=1), HT.TD(width=4), HT.TD(filterBox, scoreBox, NOWRAP=1)), HT.TR(HT.TD(redundantBox, align="right", NOWRAP=1), HT.TD(width=10), HT.TD("Non-redundant SNP Only", NOWRAP=1)), HT.TR(HT.TD(diffAlleles, align="right", NOWRAP=1),HT.TD(width=10), HT.TD("Different Alleles Only", NOWRAP=1)) ) paddingTable.append( HT.TR(HT.TD(paddingTab1), HT.TD("", width="0"), HT.TD(paddingTab2),HT.TD(width=0), HT.TD(paddingTab3), valign="top") ) newPaddingForm = HT.Form(cgi=os.path.join(webqtlConfig.CGIDIR, self._scriptfile), enctype="multipart/form-data", name="newSNPPadding", submit=HT.Input(type="hidden"), onSubmit="Javascript:set_customStrains_cookie();") newPaddingForm.append(paddingTable) return newPaddingForm # This grabs the data from MySQL for display in the table, allowing different sorting options based on the options chosen by the user. # The base option is what kind of variant the user is looking for; the other options are nested within that base option here. def genSnpTable(self, opt): # Grabs the Gene info, regardless of the variant type searched. This means you can display it for InDels, Snps, Etc. # initialize variables tblobj={} # build dict for genTableObj function; keys include header and body tblobj_header = [] # value of key 'header' tblobj_body=[] # value of key 'body' snpHeaderRow=[] # header row list for tblobj_header (html part) headerList=[] # includes all headers' name except for strain's value strainNameRow=[] # header row list for strain names strainList=[] # includes all strains' value strainNameList0=[] strainNameList=[] geneNameList=[] # for SNP's Gene column geneIdNameDict={} domain2='' headerStyle="fs13 fwb ffl b1 cw cbrb"# style of the header cellColorStyle = "fs13 b1 fwn c222" # style of the cells if opt.geneName: self.cursor.execute("SELECT geneSymbol, chromosome, txStart, txEnd from GeneList where SpeciesId= 1 and geneSymbol = %s", opt.geneName) result = self.cursor.fetchone() if result: opt.geneName, opt.chromosome, opt.startMb, opt.endMb = result else: # If GeneName doesn't turn up results, then we'll start looking through SnpAll or Variants to check for other search types (e.g. Rs#, SnpName, or InDel Name) if opt.variant == "SNP": if opt.geneName[:2] == 'rs': self.cursor.execute("SELECT Id, Chromosome, Position, Position+0.000001 from SnpAll where Rs = %s", opt.geneName) else: self.cursor.execute("SELECT Id, Chromosome, Position, Position+0.000001 from SnpAll where SpeciesId= 1 and SnpName=%s",opt.geneName) result_snp = self.cursor.fetchall() if result_snp: self.snp_list = [v[0] for v in result_snp] opt.chromosome = result_snp[0][1]; opt.startMb = result_snp[0][2] opt.endMb = result_snp[0][3] else: return # Searches through indels by the InDel name. elif opt.variant == "InDel": if opt.geneName[0] == 'I': self.cursor.execute("SELECT Id, Chromosome, Mb_start, Mb_end FROM IndelAll WHERE SpeciesId=1 AND Name=%s", opt.geneName) result_snp = self.cursor.fetchall() if result_snp: self.snp_list = [v[0] for v in result_snp] opt.chromosome = result_snp[0][1]; opt.startMb = result_snp[0][2] opt.endMb = result_snp[0][3] else: return if (opt.variant == "SNP"): #NL 05/13/2010: update query based on new db structure in SnpAll and SnpPattern query1 = """ SELECT a.*,b.* from SnpAll a, SnpPattern b where a.SpeciesId = 1 and a.Chromosome = '%s' AND a.Position >= %.6f and a.Position < %.6f AND a.Id = b.SnpId order by a.Position """ elif (opt.variant == "InDel"): query1 = """ SELECT distinct a.Name, a.Chromosome, a.SourceId, a.Mb_start, a.Mb_end, a.Strand, a.Type, a.Size, a.InDelSequence, b.Name from IndelAll a, SnpSource b where a.SpeciesId = '1' and a.Chromosome = '%s' AND a.Mb_start >= %2.6f and a.Mb_start < (%2.6f+.0010) AND b.Id = a.SourceId order by a.Mb_start """ self.cursor.execute(query1 % (opt.chromosome, opt.startMb, opt.endMb)) results_all = self.cursor.fetchall() # This executes the query if CHR, MB_START, MB_END are chosen as the search terms and Gene/SNP is not used results = self.filterResults(results_all, opt) # output xls file's name opt.xslFilename = "SNP_Chr%s_%2.6f-%2.6f" % (opt.chromosome, opt.startMb, opt.endMb) nnn = len(results) if nnn == 0: return nnn, "" elif nnn > self.MAXSNPRETURN: gifmap=self.snpDensityMap(opt,query1,results_all) #07-28-2011 updated by NL: added info part for snp density map Info="Because the number of results exceeds the limit of 5000, the selected region could not be displayed. " Info2="Please select a smaller region by clicking the rectangle corresponding with its location in the map below." densityMap =HT.Span(Info,HT.BR(),Info2,HT.BR(),HT.BR(),gifmap, HT.Image('/image/'+opt.xslFilename+'.png', border=0, usemap='#SNPImageMap'),Class='fwb fs14') return nnn, densityMap else: pass ############## # Excel file # ############## # This code is for making the excel output file if opt.xls: opt.xslFilename += ".xls" # Create a new Excel workbook workbook = xl.Writer(os.path.join(webqtlConfig.TMPDIR, opt.xslFilename)) worksheet = workbook.add_worksheet() titleStyle = workbook.add_format(align = 'left', bold = 0, size=18, border = 1, border_color="gray") headingStyle = workbook.add_format(align = 'center', bold = 1, size=13, fg_color = 0x1E, color="white", border = 1, border_color="gray") headingStyle2 = workbook.add_format(align = 'center', bold = 1, size=13, fg_color = 0x1E, color="white", rotation = 2, border = 1, border_color="gray") XLSBASECOLORS0 = {"A": "red", "C": 0x18, "T": 0x22, "G": "green", "-": 0x21, "":0x2F} XLSBASECOLORS = {} for key in XLSBASECOLORS0.keys(): XLSBASECOLORS[key] = workbook.add_format(align = 'center', size=12, fg_color = XLSBASECOLORS0[key], border = 1, border_color="gray") ##Write xls's title Info worksheet.write([0, 0], "GeneNetwork Variant Browser", titleStyle) worksheet.write([1, 0], "%s%s" % (webqtlConfig.PORTADDR, os.path.join(webqtlConfig.CGIDIR, self._scriptfile))) worksheet.write([2, 0], "Date : %s" % time.strftime("%B %d, %Y", time.gmtime())) worksheet.write([3, 0], "Time : %s GMT" % time.strftime("%H:%M ", time.gmtime())) worksheet.write([4, 0], "Search by : %s" % self.remote_ip) if opt.geneName: worksheet.write([5, 0], "Search term : %s" % opt.geneName) else: worksheet.write([5, 0], "view region : Chr %s %2.6f - %2.6f Mb" % (opt.chromosome, opt.startMb, opt.endMb)) nTitleRow = 7 #NL: new way to get header info for each variant # The next line determines which columns HEADERS show up in the table, depending on which Variant is selected to search the table for. This is for the column HEADERS ONLY; not the data displayed (that comes later). if (opt.variant == "SNP"): headerList=['Index','SNP ID','Chr','Mb','Alleles','Source','ConScore','Gene','Transcript','Exon','Domain 1','Domain 2','Function','Details'] elif (opt.variant == "InDel"): headerList=['Index','ID','Type','InDel Chr','Mb Start','Mb End','Strand','Size','Sequence','Source'] if headerList: for ncol, item in enumerate(headerList): if ncol==0: snpHeaderRow.append(THCell(HT.TD(item, Class=headerStyle, valign='bottom',nowrap='ON'),sort=0)) elif item=="Details" or item=="Function" : snpHeaderRow.append(THCell(HT.TD(HT.Href(text = HT.Span(item, HT.Sup(' ?', style="color:#f00"),Class=headerStyle), target = '_blank',url = "/snpbrowser.html#%s"%item), Class=headerStyle, valign='bottom',nowrap='ON'), text=item, idx=ncol)) else: snpHeaderRow.append(THCell(HT.TD(item, Class=headerStyle, valign='bottom',nowrap='ON'),text=item, idx=ncol)) #excel file for table headers' names worksheet.write([nTitleRow, ncol], item, headingStyle) # This writes the strain column names for the SNPs. The other variants only have data for C57BL6 and DBA2J, so they don't need this information. if (opt.variant == "SNP"): if opt.customStrain: strainNameList = [v for v in opt.chosenStrains] strainNameList = filter((lambda x: x[0]>=0),strainNameList) else: strainNameList=opt.allStrainNamesPair for j, item in enumerate(strainNameList): _contents = [] for char in item[0]: _contents += [char, HT.BR()] if j % 5 == 0: strainNameRow.append(THCell(HT.TD(contents =_contents, Class="fs12 fwn ffl b1 cw cbrb", width=2, align="Center", valign="bottom", style="border-left:2px solid black"),sort=0)) else: strainNameRow.append(THCell(HT.TD(contents =_contents, Class="fs12 fwn ffl b1 cw cbrb", width=2, align="Center", valign="bottom"),sort=0)) #excel file ncol += 1 worksheet.write([nTitleRow, ncol], item[0], headingStyle2) worksheet.set_column([ncol, ncol], 3) snpHeaderRow.extend(strainNameRow) tblobj_header.append(snpHeaderRow) tblobj['header']=tblobj_header #Changes text color of SNP label background. The colors here (e.g. cbgdull) are defined in ../css/general.css BASECOLORS = {"A": "cbrdull", "C": "cbbdull", "T": "cbydull", "G": "cbgdull", "-": "cbpdull", "":"cbccc","t": "cbg22t", "c": "cbg22c", "a": "cbg22a", "g": "cbg22g"} # # Code for determining if SNPs are identical (if the location of one SNP is the same as the SNP after it) try: self.cursor.execute(query1 % (opt.chromosome, 0, opt.startMb) + " desc limit 1") firstMb = self.cursor.fetchone() except: firstMb =0 if firstMb: lastMb = firstMb[5] else: lastMb = 0 # get geneId Name pair for SNP result if opt.variant == "SNP": for item in results: if item[5]: geneName=item[5][1] # eliminate the duplicate geneName if geneName and (geneName not in geneNameList): geneNameList.append(geneName) if len(geneNameList)>0: geneIdNameDict=self.getGeneIdNameDict(geneNameList) # This pulls out the 'results' variable and splits it into the sequence of results. for seq, result in enumerate(results): result = list(result) if opt.variant == "SNP": SnpName, Rs, Chromosome, Mb, Alleles, gene, transcript, exon, domainList, function, functionDetails,SnpSource,ConScore,SnpId = result[:14] strainNameList=result[14:] #if domain is intergenic, there's no gene, transcript,exon,function,functionDetails info if Rs: SnpHref = HT.Href(text=Rs, url=webqtlConfig.DBSNP % (Rs), target="_blank") SnpName = Rs else: startBp=int(Mb*1000000 -100) endBp=int(Mb*1000000 +100) positionInfo="chr%s:%d-%d"%(Chromosome,startBp,endBp) SnpHref = HT.Href(text=SnpName,url=webqtlConfig.GENOMEBROWSER_URL % (positionInfo), Class="fs12 fwn",target="_blank") Mb=float(Mb) MbFormatted = "%2.6f" % Mb if SnpSource=='Sanger/UCLA': sourceURL1="http://www.sanger.ac.uk/resources/mouse/genomes/" sourceURL2="http://mouse.cs.ucla.edu/mousehapmap/beta/wellcome.html" SnpSourceLink=HT.Href(text="Sanger", url=sourceURL1, Class="fs12 fwn",target="_blank") SnpSourceLink1= HT.Href(text="UCLA", url=sourceURL2, Class="fs12 fwn",target="_blank") else: SnpSourceLink="" if not ConScore: ConScore='' if gene: geneName=gene[1] # if geneName has related geneId, then use geneId for NCBI search if geneIdNameDict.has_key(geneName) and geneIdNameDict[geneName]: geneId=geneIdNameDict[gene[1]] ncbiUrl = HT.Href(text="NCBI",target='_blank',url=webqtlConfig.NCBI_LOCUSID % geneId, Class="fs10 fwn") else:# if geneName can not find related geneId, then use geneName for NCBI search ncbiUrl = HT.Href(text="NCBI",target='_blank',url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?CMD=search&DB=gene&term=%s" % geneName, Class="fs10 fwn") #GN similar trait link _Species="mouse" similarTraitUrl = "%s?cmd=sch&gene=%s&alias=1&species=%s" % (os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), geneName, _Species) gnUrl = HT.Href(text="GN",target='_blank',url=similarTraitUrl, Class="fs10 fwn") else: geneName='' ncbiUrl='' gnUrl='' if geneName: geneNameCol=HT.TD(HT.Italic(geneName), HT.BR(),gnUrl," | ", ncbiUrl, Class=cellColorStyle,nowrap='ON') else: geneNameCol=HT.TD(Class=cellColorStyle,nowrap='ON') if transcript: transcriptHref=HT.Href(text=transcript, url=webqtlConfig.ENSEMBLETRANSCRIPT_URL % (transcript), Class="fs12 fwn",target="_blank") else: transcriptHref=transcript if exon: exon=exon[1]#exon[0] is exonId;exon[1] is exonRank else: exon='' if domainList: domain=domainList[0] domain2=domainList[1] if domain=='Exon': domain=domain+" "+exon funcList=[] if functionDetails: funcList=string.split(string.strip(functionDetails),',') funcList=map(string.strip,funcList) funcList[0]=funcList[0].title() functionDetails=', '.join(item for item in funcList) functionDetails=functionDetails.replace("_", " "); functionDetails=functionDetails.replace("/", " -> "); if functionDetails=="Biotype: Protein Coding": functionDetails =functionDetails+", Coding Region Unknown" # build SnpRow for SNP basic information\ SnpRow=[] # first column of table SnpRow.append(TDCell(HT.TD(HT.Input(type="checkbox", Class="checkbox", name="index",value=seq+1, onClick="highlight(this)"), align='right',Class=cellColorStyle,nowrap='ON'),text=seq+1)) SnpRow.append(TDCell(HT.TD(SnpHref, Class=cellColorStyle,nowrap='ON'),SnpName, SnpName)) SnpRow.append(TDCell(HT.TD(Chromosome, Class=cellColorStyle, align="center",nowrap='ON'),Chromosome, Chromosome)) SnpRow.append(TDCell(HT.TD(MbFormatted, Class=cellColorStyle, align="center",nowrap='ON'),MbFormatted, MbFormatted)) SnpRow.append(TDCell(HT.TD(Alleles, Class=cellColorStyle, align="center",nowrap='ON'),Alleles, Alleles)) if SnpSource=='Sanger/UCLA': SnpRow.append(TDCell(HT.TD(SnpSourceLink,'/',SnpSourceLink1, Class=cellColorStyle,nowrap='ON'),SnpSource, SnpSource)) else: SnpRow.append(TDCell(HT.TD(SnpSource, Class=cellColorStyle,nowrap='ON'),SnpSource, SnpSource)) SnpRow.append(TDCell(HT.TD(ConScore, Class=cellColorStyle,align="center",nowrap='ON'),ConScore, ConScore)) SnpRow.append(TDCell(geneNameCol,geneName, geneName)) SnpRow.append(TDCell(HT.TD(transcriptHref, Class=cellColorStyle,nowrap='ON'),transcript, transcript)) SnpRow.append(TDCell(HT.TD(exon, Class=cellColorStyle,align="center",nowrap='ON'),exon, exon)) SnpRow.append(TDCell(HT.TD(domain, Class=cellColorStyle, align="center",nowrap='ON'),domain, domain)) SnpRow.append(TDCell(HT.TD(domain2, Class=cellColorStyle, align="center",nowrap='ON'),domain2, domain2)) SnpRow.append(TDCell(HT.TD(function, Class=cellColorStyle,nowrap='ON'),function, function)) SnpRow.append(TDCell(HT.TD(functionDetails, Class=cellColorStyle,nowrap='ON'),functionDetails, functionDetails)) # excel file worksheet.write([nTitleRow+seq+1, 0], seq+1) worksheet.write([nTitleRow+seq+1, 1], SnpName) worksheet.write([nTitleRow+seq+1, 2], Chromosome) worksheet.write([nTitleRow+seq+1, 3], MbFormatted) worksheet.write([nTitleRow+seq+1, 4], Alleles) worksheet.write([nTitleRow+seq+1, 5], SnpSource) worksheet.write([nTitleRow+seq+1, 6], ConScore) worksheet.write([nTitleRow+seq+1, 7], geneName) worksheet.write([nTitleRow+seq+1, 8], transcript) worksheet.write([nTitleRow+seq+1, 9], exon) worksheet.write([nTitleRow+seq+1, 10], domain) worksheet.write([nTitleRow+seq+1, 11], domain2) worksheet.write([nTitleRow+seq+1, 12], function) worksheet.write([nTitleRow+seq+1, 13], functionDetails) #ncol here should be the last ncol + 1 ncol = 14 # This puts the Allele data into the table if SNP is selected BASE="" bcolor = 'fs13 b1 cbw c222' for j , item in enumerate(strainNameList): if item: BASE =item bcolor = BASECOLORS[BASE] + " b1" else: BASE = "" bcolor = 'fs13 b1 cbeee c222' #This changes text color of SNPs if j % 5 == 0: SnpRow.append(TDCell(HT.TD(BASE, Class=bcolor, align="center", style="border-left:2px solid black"),BASE,BASE)) else: SnpRow.append(TDCell(HT.TD(BASE, Class=bcolor, align="center"),BASE,BASE)) # #excel for strains' value if BASE in XLSBASECOLORS.keys(): xbcolor = XLSBASECOLORS[BASE] else: xbcolor = XLSBASECOLORS[""] worksheet.write([nTitleRow+seq+1, ncol], BASE, xbcolor) ncol += 1 tblobj_body.append(SnpRow) lastMb = Mb elif opt.variant == "InDel": indelName, indelChr, indelMb_s, indelMb_e, indelStrand, indelType, indelSize, indelSequence, sourceName = result # build SnpRow for Indel basic information\ SnpRow=[] # first column of table SnpRow.append(TDCell(HT.TD(HT.Input(type="checkbox", Class="checkbox", name="index",value=seq+1, onClick="highlight(this)"), align='right',Class=cellColorStyle,nowrap='ON'),text=seq+1)) SnpRow.append(TDCell(HT.TD(indelName, Class=cellColorStyle,nowrap='ON'),indelName, indelName))# Name of the InDel (e.g. Indel_1350) SnpRow.append(TDCell(HT.TD(indelType, Class=cellColorStyle, align="center",nowrap='ON'),indelType, indelType))# E.g. Insertion or Deletion SnpRow.append(TDCell(HT.TD(indelChr, Class=cellColorStyle, align="center",nowrap='ON'),indelChr, indelChr))# Indel Chromosome (e.g. 1) SnpRow.append(TDCell(HT.TD(indelMb_s, Class=cellColorStyle, align="center",nowrap='ON'),indelMb_s, indelMb_s)) SnpRow.append(TDCell(HT.TD(indelMb_e, Class=cellColorStyle, align="center",nowrap='ON'),indelMb_e, indelMb_e)) SnpRow.append(TDCell(HT.TD(indelStrand, Class=cellColorStyle, align="center",nowrap='ON'),indelStrand, indelStrand)) SnpRow.append(TDCell(HT.TD(indelSize, Class=cellColorStyle,align="center",nowrap='ON'),indelSize, indelSize)) SnpRow.append(TDCell(HT.TD(indelSequence, Class=cellColorStyle,align="center",nowrap='ON'),indelSequence, indelSequence)) SnpRow.append(TDCell(HT.TD(sourceName, Class=cellColorStyle,nowrap='ON'),sourceName, sourceName)) if opt.xls: worksheet.write([nTitleRow+seq+1,0], seq+1) worksheet.write([nTitleRow+seq+1,1], indelName) worksheet.write([nTitleRow+seq+1,2], indelType) worksheet.write([nTitleRow+seq+1,3], indelChr) worksheet.write([nTitleRow+seq+1,4], indelMb_s) worksheet.write([nTitleRow+seq+1,5], indelMb_e) worksheet.write([nTitleRow+seq+1,6], indelStrand) worksheet.write([nTitleRow+seq+1,7], indelSize) worksheet.write([nTitleRow+seq+1,8], indelSequence) worksheet.write([nTitleRow+seq+1,9], sourceName) tblobj_body.append(SnpRow) else: pass tblobj['body']=tblobj_body workbook.close() # close here is important, otherwise xls file will not be generated return len(results), tblobj # initialize the value of start Mb and end Mb def initialMb(self): try: startMb = abs(float(self.formdata.getfirst("start", "30.1"))) endMb = abs(float(self.formdata.getfirst("end", "30.12"))) except: startMb = endMb = 30.0 if startMb > endMb: temp = endMb endMb = startMb startMb = temp if startMb == endMb: endMb = startMb + 2 # DO NOT MAKE THIS LESS THAN 2 MB. YOU WILL BREAK EVERYTHING BECAUSE NO DEFAULT VARIANT IS SELECTED if endMb - startMb > self.MAXMB: endMb = self.MAXMB + startMb return startMb,endMb # get customStrains from cookie def retrieveCustomStrains(self,fd): cookie = fd.cookies custom_strains = [] if cookie.has_key('customstrains1') and cookie['customstrains1']: strain_cookie = cookie['customstrains1'] alloptions = string.split(strain_cookie,',') for one in alloptions: sname_value = string.split(one,':') if len(sname_value) == 2: custom_strains.append( (sname_value[0],sname_value[0])) else: custom_strains=[('C57BL/6J', 'C57BL/6J'),('DBA/2J','DBA/2J'),('A/J','A/J'),('129S1/SvImJ','129S1/SvImJ'),('NOD/ShiLtJ','NOD/ShiLtJ'),('NZO/HlLtJ','NZO/HlLtJ'),('WSB/EiJ','WSB/EiJ'),('PWK/PhJ','PWK/PhJ'),('CAST/EiJ','CAST/EiJ')] return custom_strains # get geneId Name pair, key is geneName, value is geneId def getGeneIdNameDict(self, geneNameList): geneIdNameDict={} if len(geneNameList)==0: return "" geneNameStrList =["'"+geneName+"'" for geneName in geneNameList] geneNameStr=string.join(geneNameStrList,',') query = """ SELECT geneId, geneSymbol from GeneList where SpeciesId=1 and geneSymbol in (%s) """ % geneNameStr self.cursor.execute(query) results = self.cursor.fetchall() if len(results)>0: for item in results: geneIdNameDict[item[1]]=item[0] else: pass return geneIdNameDict # This grabs the mySQL query results and filters them for use when SNP Variants are searched for. def filterResults(self, results, opt): filtered = [] strainIdexList=[] last_mb = -1 if opt.customStrain and opt.chosenStrains: for item in opt.chosenStrains: index =opt.allStrainNameList.index(item[0]) strainIdexList.append(index) for seq, result in enumerate(results): result = list(result) if opt.variant == "SNP": displayStains=[] # The order of variables here is the order they are selected from in genSnpTable SnpId,SpeciesId,SnpName, Rs, Chromosome, Mb, Alleles, SnpSource,ConservationScore = result[:9] effct =result[9:25] #result[25] is SnpId; opt.alleleValueList =result[26:] if opt.customStrain and opt.chosenStrains: for index in strainIdexList: displayStains.append(result[26+index]) opt.alleleValueList =displayStains effectInfoDict=self.getEffectInfo(effct) codingDomainList=['Start Gained','Start Lost','Stop Gained','Stop Lost','Nonsynonymous','Synonymous'] intronDomainList=['Splice Site','Nonsplice Site'] for key in effectInfoDict: if key in codingDomainList: domain=['Exon','Coding'] elif key in ['3\' UTR','5\' UTR']: domain=['Exon',key] elif key in ['Unknown Effect In Exon']: domain=['Exon',''] elif key in intronDomainList: domain=['Intron',key] else: domain =[key,''] if 'Intergenic' in domain: gene='' transcript='' exon='' function='' functionDetails='' if not opt.redundant or last_mb != Mb: # filter redundant or not if self.filterIn(domain, function,SnpSource, ConservationScore,opt): generalInfoList =[SnpName, Rs, Chromosome, Mb, Alleles, gene,transcript,exon,domain,function,functionDetails,SnpSource,ConservationScore,SnpId] generalInfoList.extend(opt.alleleValueList) filtered.append(generalInfoList) last_mb = Mb else: geneList,transcriptList,exonList,functionList,functionDetailsList=effectInfoDict[key] for index, item in enumerate(geneList): gene=item transcript=transcriptList[index] if exonList: exon=exonList[index] else: exon="" if functionList: function=functionList[index] if function=='Unknown Effect In Exon': function="Unknown" else: function="" if functionDetailsList: functionDetails='Biotype: '+functionDetailsList[index] else: functionDetails="" if not opt.redundant or last_mb != Mb: # filter redundant or not if self.filterIn(domain, function,SnpSource, ConservationScore,opt): generalInfoList =[SnpName, Rs, Chromosome, Mb, Alleles, gene,transcript,exon,domain,function,functionDetails,SnpSource,ConservationScore,SnpId] generalInfoList.extend(opt.alleleValueList) filtered.append(generalInfoList) last_mb = Mb elif opt.variant =="InDel": # The ORDER of variables here IS IMPORTANT. # THIS IS FOR ANYTHING YOU BRING OUT OF THE VARIANT TABLE USING InDel indelName, indelChr, sourceId, indelMb_s, indelMb_e, indelStrand, indelType, indelSize, indelSequence, sourceName = result indelType=indelType.title() if not opt.redundant or last_mb != indelMb_s: # filter redundant or not gene = "No Gene" domain = ConservationScore = SnpId = SnpName = Rs = flank3 =flank5 = ncbi =function = '' if self.filterIn(domain, function,sourceName , ConservationScore, opt): filtered.append([indelName, indelChr, indelMb_s, indelMb_e, indelStrand, indelType, indelSize, indelSequence, sourceName]) last_mb = indelMb_s else: filtered.append(result) return filtered # decide whether need to add this record or not def filterIn(self, domain, function, SnpSource,ConservationScore,opt): domainSatisfied = True functionSatisfied = True differentAllelesSatisfied = True sourceSatisfied= True if domain: if len(domain) == 0: if opt.domain[0] != "": # unknown and not searching for "All" domainSatisfied = False #True else: domainSatisfied = False for onechoice in opt.domain: if domain[0].startswith(onechoice) or domain[1].startswith(onechoice): domainSatisfied = True else: if opt.domain[0] != "": # when the info is unknown but the users is not searching for "All" domainSatisfied = False if SnpSource: if len(SnpSource) ==0: # not available if len(opt.source[0]) > 0: # and not searching for "All" sourceSatisfied = False #True else: sourceSatisfied = False for choice in opt.source: if SnpSource.startswith(choice): sourceSatisfied = True else: if len(opt.source[0]) > 0: # when the source is unknown but the users is not searching for "All" sourceSatisfied = False if function: if len(function) ==0: # not available if len(opt.function[0]) > 0: # and not searching for "All" functionSatisfied = False #True else: functionSatisfied = False for choice in opt.function: if function.startswith(choice): functionSatisfied = True else: if len(opt.function[0]) > 0: # when the function is unknown but the users is not searching for "All" functionSatisfied = False if ConservationScore: con_score = float(ConservationScore) if len(opt.score) > 0: opt_score_float = float(opt.score) else: opt_score_float = 0.0 if opt.conservationCriteria == '>=': if con_score >= opt_score_float: scoreSatisfied = True else: scoreSatisfied = False elif opt.conservationCriteria == '==': if con_score == opt_score_float: scoreSatisfied = True else: scoreSatisfied = False elif opt.conservationCriteria == '<=': if con_score <= opt_score_float: scoreSatisfied = True else: scoreSatisfied = False else: if float(opt.score)>0: scoreSatisfied = False else: scoreSatisfied = True # allow null value # when diffAlleles function has been chose; # decide whether need to show this record based on strains' allele value if opt.variant == "SNP" and opt.diffAlleles: totalCount =0 aList=[] for x in opt.alleleValueList: if x and (x.lower() not in aList) and ( x != "-"): aList.append(x.lower()) totalCount= len(aList) if totalCount <= 1: differentAllelesSatisfied= False else: differentAllelesSatisfied= True else: differentAllelesSatisfied = True return domainSatisfied and functionSatisfied and sourceSatisfied and scoreSatisfied and differentAllelesSatisfied #snpDensityMap will display when the max return is greater than default value # pay attention to the order of drawing canvas, the latter one will overlap the former one def snpDensityMap(self,opt,query,results): snpCanvas = pid.PILCanvas(size=(900,200)) xLeftOffset, xRightOffset, yTopOffset, yBottomOffset = (30, 30, 40, 50) cWidth = snpCanvas.size[0] cHeight = snpCanvas.size[1] plotWidth = cWidth - xLeftOffset - xRightOffset plotHeight = cHeight - yTopOffset - yBottomOffset yZero = yTopOffset + plotHeight/2 plotXScale = plotWidth/(opt.endMb - opt.startMb) #draw clickable map #Image map gifmap = HT.Map(name='SNPImageMap') NCLICK = 80.0 clickStep = plotWidth/NCLICK clickMbStep = (opt.endMb - opt.startMb)/NCLICK for i in range(NCLICK): #updated by NL 07-11-2011: change the parameters to make clickable function work properly. HREF = os.path.join(webqtlConfig.CGIDIR, "%s&submitStatus=1&diffAlleles=True&customStrain=True"%self._scriptfile) + \ "&chr=%s&start=%2.6f&end=%2.6f" % (opt.chromosome, opt.startMb+i*clickMbStep, opt.startMb+(i+1)*clickMbStep) COORDS0 = (xLeftOffset+i*clickStep, yTopOffset-18, xLeftOffset+(i+1)*clickStep-2, yTopOffset+plotHeight) snpCanvas.drawRect(COORDS0[0],COORDS0[1],COORDS0[2],COORDS0[3], edgeColor=pid.white) COORDS0 = "%d,%d,%d,%d" % COORDS0 Areas1 = HT.Area(shape='rect',coords=COORDS0,href=HREF) gifmap.areas.append(Areas1) COORDS = (xLeftOffset+i*clickStep, yTopOffset-18, xLeftOffset+(i+1)*clickStep-2, yTopOffset-10) snpCanvas.drawRect(COORDS[0],COORDS[1],COORDS[2],COORDS[3]+5, edgeColor=pid.wheat, fillColor=pid.wheat) COORDS = "%d,%d,%d,%d" % COORDS Areas = HT.Area(shape='rect',coords=COORDS) gifmap.areas.append(Areas) snpCanvas.drawString("Click to view the corresponding section of the SNP map", xLeftOffset, yTopOffset-25, font=pid.Font(ttf="verdana", size=14, bold=0), color=pid.black) ###draw SNPs snpCounts = [] stepMb = 1.0/plotXScale startMb = opt.startMb for i in range(plotWidth): self.cursor.execute(query % (opt.chromosome, startMb, startMb + stepMb)) snpCounts.append(len(self.cursor.fetchall())) startMb += stepMb maxCounts = max(snpCounts) sfactor = plotHeight/(2.0*maxCounts) for i in range(plotWidth): sheight = sfactor*snpCounts[i] snpCanvas.drawLine(i+xLeftOffset, yZero-sheight, i+xLeftOffset, yZero+sheight, color = pid.orange) ###draw X axis snpCanvas.drawLine(xLeftOffset, yZero, xLeftOffset+plotWidth, yZero, color=pid.black) XScale = Plot.detScale(opt.startMb, opt.endMb) XStart, XEnd, XStep = XScale if XStep < 8: XStep *= 2 spacingAmtX = spacingAmt = (XEnd-XStart)/XStep j = 0 while abs(spacingAmtX -int(spacingAmtX)) >= spacingAmtX/100.0 and j < 6: j += 1 spacingAmtX *= 10 formatStr = '%%2.%df' % j MBLabelFont = pid.Font(ttf="verdana", size=12, bold=0) NUM_MINOR_TICKS = 5 xMinorTickHeight = 4 xMajorTickHeight = 5 for counter, _Mb in enumerate(Plot.frange(XStart, XEnd, spacingAmt / NUM_MINOR_TICKS)): if _Mb < opt.startMb or _Mb > opt.endMb: continue Xc = xLeftOffset + plotXScale*(_Mb - opt.startMb) if counter % NUM_MINOR_TICKS == 0: # Draw a MAJOR mark, not just a minor tick mark snpCanvas.drawLine(Xc, yZero, Xc, yZero+xMajorTickHeight, width=2, color=pid.black) # Draw the MAJOR tick mark labelStr = str(formatStr % _Mb) # What Mbase location to put on the label strWidth = snpCanvas.stringWidth(labelStr, font=MBLabelFont) drawStringXc = (Xc - (strWidth / 2.0)) snpCanvas.drawString(labelStr, drawStringXc, yZero +20, font=MBLabelFont, angle=0, color=pid.black) else: snpCanvas.drawLine(Xc, yZero, Xc, yZero+xMinorTickHeight, color=pid.black) # Draw the MINOR tick mark # end else xLabelFont = pid.Font(ttf="verdana", size=20, bold=0) xLabel = "SNP Density Map : Chr%s %2.6f-%2.6f Mb" % (opt.chromosome, opt.startMb, opt.endMb) snpCanvas.drawString(xLabel, xLeftOffset + (plotWidth -snpCanvas.stringWidth(xLabel, font=xLabelFont))/2, yTopOffset +plotHeight +30, font=xLabelFont, color=pid.black) snpCanvas.save(os.path.join(webqtlConfig.IMGDIR, opt.xslFilename), format='png') return gifmap #NL 05-13-2011: rewrite to get field_names in query def getStrainNamePair(self): # add by NL ^-^ 05-13/2011 # get field_names in query strainNamePair=[] query ='SELECT * FROM SnpPattern limit 1' self.cursor.execute(query) num_fields = len(self.cursor.description) field_names = [i[0] for i in self.cursor.description] strainsNameList=field_names[1:] # index for strain name starts from 1 for index, name in enumerate(strainsNameList): strainNamePair.append((name,name)) return strainNamePair def getEffectDetailsByCategory(self, effectName=None, effectValue=None): geneList=[] transcriptList=[] exonList=[] funcList=[] funcDetailList=[] tmpList=[] geneGroupList =['Upstream','Downstream','Splice Site','Nonsplice Site','3\' UTR'] biotypeGroupList=['Unknown Effect In Exon','Start Gained','Start Lost','Stop Gained','Stop Lost','Nonsynonymous','Synonymous'] newCodonGroupList=['Start Gained'] codonEffectGroupList=['Start Lost','Stop Gained','Stop Lost','Nonsynonymous','Synonymous'] # split data in effect by using '|' into groups effectDetailList = string.split(string.strip(effectValue),'|') effectDetailList = map(string.strip, effectDetailList) # if there are more than one group of data, then traversing each group and retrieve each item in the group for index, item in enumerate(effectDetailList): itemList =string.split(string.strip(item),',') itemList = map(string.strip, itemList) geneId=itemList[0] geneName=itemList[1] geneList.append([geneId,geneName]) transcriptList.append(itemList[2]) if effectName not in geneGroupList: exonId=itemList[3] exonRank=itemList[4] exonList.append([exonId,exonRank]) if effectName in biotypeGroupList: biotype=itemList[5] funcList.append(effectName) if effectName in newCodonGroupList: newCodon=itemList[6] tmpList=[biotype,newCodon] funcDetailList.append(string.join(tmpList, ", ")) elif effectName in codonEffectGroupList: old_new_AA=itemList[6] old_new_Codon=itemList[7] codon_num=itemList[8] tmpList=[biotype,old_new_AA,old_new_Codon,codon_num] funcDetailList.append(string.join(tmpList, ", ")) else: funcDetailList.append(biotype) return [geneList,transcriptList,exonList,funcList,funcDetailList] def getEffectInfo(self, effectList): Domain='' effectDetailList=[] effectInfoDict={} Prime3_UTR,Prime5_UTR,Upstream,Downstream,Intron,Nonsplice_Site,Splice_Site,Intergenic=effectList[:8] Exon,Non_Synonymous_Coding,Synonymous_Coding,Start_Gained,Start_Lost,Stop_Gained,Stop_Lost,Unknown_Effect_In_Exon=effectList[8:] if Intergenic: Domain='Intergenic' effectInfoDict[Domain]='' else: # if not Exon: # get geneList, transcriptList info. if Upstream: Domain='Upstream' effectDetailList=self.getEffectDetailsByCategory(effectName='Upstream', effectValue=Upstream) effectInfoDict[Domain]=effectDetailList if Downstream: Domain='Downstream' effectDetailList=self.getEffectDetailsByCategory(effectName='Downstream', effectValue=Downstream) effectInfoDict[Domain]=effectDetailList if Intron: if Splice_Site: Domain='Splice Site' effectDetailList=self.getEffectDetailsByCategory(effectName='Splice Site', effectValue=Splice_Site) effectInfoDict[Domain]=effectDetailList if Nonsplice_Site: Domain='Nonsplice Site' effectDetailList=self.getEffectDetailsByCategory(effectName='Nonsplice Site', effectValue=Nonsplice_Site) effectInfoDict[Domain]=effectDetailList # get gene, transcriptList and exon info. if Prime3_UTR: Domain='3\' UTR' effectDetailList=self.getEffectDetailsByCategory(effectName='3\' UTR', effectValue=Prime3_UTR) effectInfoDict[Domain]=effectDetailList if Prime5_UTR: Domain='5\' UTR' effectDetailList=self.getEffectDetailsByCategory(effectName='5\' UTR', effectValue=Prime5_UTR) effectInfoDict[Domain]=effectDetailList if Start_Gained: Domain='5\' UTR' effectDetailList=self.getEffectDetailsByCategory(effectName='Start Gained', effectValue=Start_Gained) effectInfoDict[Domain]=effectDetailList if Unknown_Effect_In_Exon: Domain='Unknown Effect In Exon' effectDetailList=self.getEffectDetailsByCategory(effectName='Unknown Effect In Exon', effectValue=Unknown_Effect_In_Exon) effectInfoDict[Domain]=effectDetailList if Start_Lost: Domain='Start Lost' effectDetailList=self.getEffectDetailsByCategory(effectName='Start Lost', effectValue=Start_Lost) effectInfoDict[Domain]=effectDetailList if Stop_Gained: Domain='Stop Gained' effectDetailList=self.getEffectDetailsByCategory(effectName='Stop Gained', effectValue=Stop_Gained) effectInfoDict[Domain]=effectDetailList if Stop_Lost: Domain='Stop Lost' effectDetailList=self.getEffectDetailsByCategory(effectName='Stop Lost', effectValue=Stop_Lost) effectInfoDict[Domain]=effectDetailList if Non_Synonymous_Coding: Domain='Nonsynonymous' effectDetailList=self.getEffectDetailsByCategory(effectName='Nonsynonymous', effectValue=Non_Synonymous_Coding) effectInfoDict[Domain]=effectDetailList if Synonymous_Coding: Domain='Synonymous' effectDetailList=self.getEffectDetailsByCategory(effectName='Synonymous', effectValue=Synonymous_Coding) effectInfoDict[Domain]=effectDetailList return effectInfoDict def getSortedStrainList(self, strainList): sortedStrainList=[] removeList=['C57BL/6J','DBA/2J'] for item in removeList: strainList.remove(item) sortedStrainList=removeList+strainList return sortedStrainList # build header and footer parts for export excel file def createExcelFileWithTitleAndFooter(self, workbook=None, datasetName=None,returnNumber=None): worksheet = workbook.add_worksheet() titleStyle = workbook.add_format(align = 'left', bold = 0, size=14, border = 1, border_color="gray") ##Write title Info worksheet.write([1, 0], "Citations: Please see %s/reference.html" % webqtlConfig.PORTADDR, titleStyle) worksheet.write([2, 0], "Dataset : %s" % datasetName, titleStyle) worksheet.write([3, 0], "Date : %s" % time.strftime("%B %d, %Y", time.gmtime()), titleStyle) worksheet.write([4, 0], "Time : %s GMT" % time.strftime("%H:%M ", time.gmtime()), titleStyle) worksheet.write([5, 0], "Status of data ownership: Possibly unpublished data; please see %s/statusandContact.html for details on sources, ownership, and usage of these data." % webqtlConfig.PORTADDR, titleStyle) #Write footer info worksheet.write([8 + returnNumber, 0], "Funding for The GeneNetwork: NIAAA (U01AA13499, U24AA13513), NIDA, NIMH, and NIAAA (P20-DA21131), NCI MMHCC (U01CA105417), and NCRR (U01NR 105417)", titleStyle) worksheet.write([9 + returnNumber, 0], "PLEASE RETAIN DATA SOURCE INFORMATION WHENEVER POSSIBLE", titleStyle) return worksheet def getSource(self): sourceQuery ="select distinct Source from SnpAll" self.cursor.execute(sourceQuery) result =self.cursor.fetchall() sourceList=[("All", "")] try: for item in result: item=item[0] sourceList.append((item,item)) except: sourceList=[] return sourceList