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Diffstat (limited to 'web/webqtl/snpBrowser/snpBrowserPage.py')
| -rwxr-xr-x | web/webqtl/snpBrowser/snpBrowserPage.py | 1259 |
1 files changed, 1259 insertions, 0 deletions
diff --git a/web/webqtl/snpBrowser/snpBrowserPage.py b/web/webqtl/snpBrowser/snpBrowserPage.py new file mode 100755 index 00000000..51132e0d --- /dev/null +++ b/web/webqtl/snpBrowser/snpBrowserPage.py @@ -0,0 +1,1259 @@ +# 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 + + |