## 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 NL 2011/02/11 # Last updated by Christian Fernandez 2012/04/07 # Refactored correlation calculation into smaller functions in preparation of # separating html from existing code import string from math import * import cPickle import os import time import pyXLWriter as xl import pp import math from htmlgen import HTMLgen2 as HT import reaper from base import webqtlConfig from utility.THCell import THCell from utility.TDCell import TDCell from base.webqtlTrait import webqtlTrait from base.webqtlDataset import webqtlDataset from base.templatePage import templatePage from utility import webqtlUtil from dbFunction import webqtlDatabaseFunction import utility.webqtlUtil #this is for parallel computing only. from correlation import correlationFunction import logging logging.basicConfig(filename="/tmp/gn_log", level=logging.INFO) _log = logging.getLogger("correlation") METHOD_SAMPLE_PEARSON = "1" METHOD_SAMPLE_RANK = "2" METHOD_LIT = "3" METHOD_TISSUE_PEARSON = "4" METHOD_TISSUE_RANK = "5" TISSUE_METHODS = [METHOD_TISSUE_PEARSON, METHOD_TISSUE_RANK] TISSUE_MOUSE_DB = 1 class AuthException(Exception): pass class Trait(object): def __init__(self, name, raw_values = None, lit_corr = None, tissue_corr = None, p_tissue = None): self.name = name self.raw_values = raw_values self.lit_corr = lit_corr self.tissue_corr = tissue_corr self.p_tissue = p_tissue self.correlation = 0 self.p_value = 0 @staticmethod def from_csv(line, data_start = 1): name = line[0] numbers = line[data_start:] # _log.info(numbers) numbers = [ float(number) for number in numbers ] return Trait(name, raw_values = numbers) def calculate_correlation(self, values, method): """Calculate the correlation value and p value according to the method specified""" #ZS: This takes the list of values of the trait our selected trait is being correlated against and removes the values of the samples our trait has no value for #There's probably a better way of dealing with this, but I'll have to ask Christian updated_raw_values = [] updated_values = [] for i in range(len(values)): if values[i] != "None": updated_raw_values.append(self.raw_values[i]) updated_values.append(values[i]) self.raw_values = updated_raw_values values = updated_values if method == METHOD_SAMPLE_PEARSON or method == METHOD_LIT or method == METHOD_TISSUE_PEARSON: corr,nOverlap = webqtlUtil.calCorrelation(self.raw_values, values, len(values)) else: corr,nOverlap = webqtlUtil.calCorrelationRank(self.raw_values, values, len(values)) self.correlation = corr self.overlap = nOverlap if self.overlap < 3: self.p_value = 1.0 else: #ZS - This is probably the wrong way to deal with this. Correlation values of 1.0 definitely exist (the trait correlated against itself), so zero division needs to br prevented. if abs(self.correlation) >= 1.0: self.p_value = 0.0 else: ZValue = 0.5*log((1.0+self.correlation)/(1.0-self.correlation)) ZValue = ZValue*sqrt(self.overlap-3) self.p_value = 2.0*(1.0 - reaper.normp(abs(ZValue))) #XZ, 01/14/2009: This method is for parallel computing only. #XZ: It is supposed to be called when "Genetic Correlation, Pearson's r" (method 1) #XZ: or "Genetic Correlation, Spearman's rho" (method 2) is selected def compute_corr( input_nnCorr, input_trait, input_list, computing_method): allcorrelations = [] for line in input_list: tokens = line.split('","') tokens[-1] = tokens[-1][:-2] #remove the last " tokens[0] = tokens[0][1:] #remove the first " traitdataName = tokens[0] database_trait = tokens[1:] if computing_method == "1": #XZ: Pearson's r corr,nOverlap = utility.webqtlUtil.calCorrelationText(input_trait, database_trait, input_nnCorr) else: #XZ: Spearman's rho corr,nOverlap = utility.webqtlUtil.calCorrelationRankText(input_trait, database_trait, input_nnCorr) traitinfo = [traitdataName,corr,nOverlap] allcorrelations.append(traitinfo) return allcorrelations def get_correlation_method_key(form_data): #XZ, 09/28/2008: if user select "1", then display 1, 3 and 4. #XZ, 09/28/2008: if user select "2", then display 2, 3 and 5. #XZ, 09/28/2008: if user select "3", then display 1, 3 and 4. #XZ, 09/28/2008: if user select "4", then display 1, 3 and 4. #XZ, 09/28/2008: if user select "5", then display 2, 3 and 5. method = form_data.formdata.getvalue("method") if method not in ["1", "2", "3" ,"4", "5"]: return "1" return method def get_custom_trait(form_data, cursor): """Pulls the custom trait, if it exists, out of the form data""" trait_name = form_data.formdata.getvalue('fullname') if trait_name: trait = webqtlTrait(fullname=trait_name, cursor=cursor) trait.retrieveInfo() return trait else: return None #XZ, 09/18/2008: get the information such as value, variance of the input strain names from the form. def get_sample_data(form_data): if form_data.allstrainlist: mdpchoice = form_data.formdata.getvalue('MDPChoice') #XZ, in HTML source code, it is "BXD Only" or "BXH only", and so on if mdpchoice == "1": strainlist = form_data.f1list + form_data.strainlist #XZ, in HTML source code, it is "MDP Only" elif mdpchoice == "2": strainlist = [] strainlist2 = form_data.f1list + form_data.strainlist for strain in form_data.allstrainlist: if strain not in strainlist2: strainlist.append(strain) #So called MDP Panel if strainlist: strainlist = form_data.f1list+form_data.parlist+strainlist #XZ, in HTML source code, it is "All Cases" else: strainlist = form_data.allstrainlist #XZ, 09/18/2008: put the trait data into dictionary form_data.allTraitData form_data.readData(form_data.allstrainlist) else: mdpchoice = None strainlist = form_data.strainlist #XZ, 09/18/2008: put the trait data into dictionary form_data.allTraitData form_data.readData() return strainlist def get_mdp_choice(form_data): if form_data.allstrainlist: return form_data.formdata.getvalue("MDPChoice") else: return None def get_species(fd, cursor): #XZ, 3/16/2010: variable RISet must be pass by the form RISet = fd.RISet #XZ, 12/12/2008: get species infomation species = webqtlDatabaseFunction.retrieveSpecies(cursor=cursor, RISet=RISet) return species def sortTraitCorrelations(traits, method="1"): if method in TISSUE_METHODS: traits.sort(key=lambda trait: trait.tissue_corr != None and abs(trait.tissue_corr), reverse=True) elif method == METHOD_LIT: traits.sort(key=lambda trait: trait.lit_corr != None and abs(trait.lit_corr), reverse=True) else: traits.sort(key=lambda trait: trait.correlation != None and abs(trait.correlation), reverse=True) return traits def auth_user_for_db(db, cursor, target_db_name, privilege, username): """Authorize a user for access to a database if that database is confidential. A db (identified by a record in ProbeSetFreeze) contains a list of authorized users who may access it, as well as its confidentiality level. If the current user's privilege level is greater than 'user', ie: root or admin, then they are automatically authed, otherwise, check the AuthorizedUsers field for the presence of their name.""" if db.type == 'ProbeSet': cursor.execute('SELECT Id, Name, FullName, confidentiality, AuthorisedUsers FROM ProbeSetFreeze WHERE Name = "%s"' % target_db_name) indId, indName, indFullName, confidential, AuthorisedUsers = cursor.fetchall()[0] if confidential: authorized = 0 #for the dataset that confidentiality is 1 #1. 'admin' and 'root' can see all of the dataset #2. 'user' can see the dataset that AuthorisedUsers contains his id(stored in the Id field of User table) if webqtlConfig.USERDICT[privilege] > webqtlConfig.USERDICT['user']: authorized = 1 else: if username in AuthorisedUsers.split(","): authorized = 1 if not authorized: raise AuthException("The %s database you selected is not open to the public at this time, please go back and select other database." % indFullName) class CorrelationPage(templatePage): corrMinInformative = 4 PAGE_HEADING = "Correlation Table" CORRELATION_METHODS = {"1" : "Genetic Correlation (Pearson's r)", "2" : "Genetic Correlation (Spearman's rho)", "3" : "SGO Literature Correlation", "4" : "Tissue Correlation (Pearson's r)", "5" : "Tissue Correlation (Spearman's rho)"} RANK_ORDERS = {"1": 0, "2": 1, "3": 0, "4": 0, "5": 1} def error(self, message, error="Error", heading = None): heading = heading or self.PAGE_HEADING return templatePage.error(heading = heading, detail = [message], error=error) def __init__(self, fd): # Call the superclass constructor templatePage.__init__(self, fd) # Connect to the database if not self.openMysql(): return # Read the genotype from a file if not fd.genotype: fd.readGenotype() sample_list = get_sample_data(fd) mdp_choice = get_mdp_choice(fd) # No idea what this is yet self.species = get_species(fd, self.cursor) #XZ, 09/18/2008: get all information about the user selected database. target_db_name = fd.formdata.getvalue('database') self.target_db_name = target_db_name try: self.db = webqtlDataset(target_db_name, self.cursor) except: detail = ["The database you just requested has not been established yet."] self.error(detail) return # Auth if needed try: auth_user_for_db(self.db, self.cursor, target_db_name, self.privilege, self.userName) except AuthException, e: detail = [e.message] return self.error(detail) #XZ, 09/18/2008: filter out the strains that have no value. self.sample_names, vals, vars, N = fd.informativeStrains(sample_list) #CF - If less than a minimum number of strains/cases in common, don't calculate anything if len(self.sample_names) < self.corrMinInformative: detail = ['Fewer than %d strain data were entered for %s data set. No calculation of correlation has been attempted.' % (self.corrMinInformative, fd.RISet)] self.error(heading=PAGE_HEADING,detail=detail) self.method = get_correlation_method_key(fd) correlation_method = self.CORRELATION_METHODS[self.method] rankOrder = self.RANK_ORDERS[self.method] # CF - Number of results returned self.returnNumber = int(fd.formdata.getvalue('criteria')) self.record_count = 0 myTrait = get_custom_trait(fd, self.cursor) # We will not get Literature Correlations if there is no GeneId because there is nothing to look against self.gene_id = int(fd.formdata.getvalue('GeneId') or 0) # We will not get Tissue Correlations if there is no gene symbol because there is nothing to look against self.trait_symbol = myTrait.symbol #XZ, 12/12/2008: if the species is rat or human, translate the geneid to mouse geneid self.input_trait_mouse_gene_id = self.translateToMouseGeneID(self.species, self.gene_id) #XZ: As of Nov/13/2010, this dataset is 'UTHSC Illumina V6.2 RankInv B6 D2 average CNS GI average (May 08)' self.tissue_probeset_freeze_id = 1 traitList = self.correlate(vals) _log.info("Done doing correlation calculation") ############################################################################################################################################ TD_LR = HT.TD(height=200,width="100%",bgColor='#eeeeee') mainfmName = webqtlUtil.genRandStr("fm_") form = HT.Form(cgi= os.path.join(webqtlConfig.CGIDIR, webqtlConfig.SCRIPTFILE), enctype='multipart/form-data', name= mainfmName, submit=HT.Input(type='hidden')) hddn = {'FormID': 'showDatabase', 'ProbeSetID': '_', 'database': self.target_db_name, 'databaseFull': self.db.fullname, 'CellID': '_', 'RISet': fd.RISet, 'identification': fd.identification} if myTrait: hddn['fullname']=fd.formdata.getvalue('fullname') if mdp_choice: hddn['MDPChoice']=mdp_choice #XZ, 09/18/2008: pass the trait data to next page by hidden parameters. webqtlUtil.exportData(hddn, fd.allTraitData) if fd.incparentsf1: hddn['incparentsf1']='ON' if fd.allstrainlist: hddn['allstrainlist'] = string.join(fd.allstrainlist, ' ') for key in hddn.keys(): form.append(HT.Input(name=key, value=hddn[key], type='hidden')) #XZ, 11/21/2008: add two parameters to form form.append(HT.Input(name="X_geneSymbol", value="", type='hidden')) form.append(HT.Input(name="Y_geneSymbol", value="", type='hidden')) #XZ, 3/11/2010: add one parameter to record if the method is rank order. form.append(HT.Input(name="rankOrder", value="%s" % rankOrder, type='hidden')) form.append(HT.Input(name="TissueProbeSetFreezeId", value="%s" % self.tissue_probeset_freeze_id, type='hidden')) #################################### # generate the info on top of page # #################################### info = self.getTopInfo(myTrait=myTrait, method=self.method, db=self.db, target_db_name=self.target_db_name, returnNumber=self.returnNumber, methodDict=self.CORRELATION_METHODS, totalTraits=traitList, identification=fd.identification ) ############## # Excel file # ############## filename= webqtlUtil.genRandStr("Corr_") xlsUrl = HT.Input(type='button', value = 'Download Table', onClick= "location.href='/tmp/%s.xls'" % filename, Class='button') # Create a new Excel workbook workbook = xl.Writer('%s.xls' % (webqtlConfig.TMPDIR+filename)) headingStyle = workbook.add_format(align = 'center', bold = 1, border = 1, size=13, fg_color = 0x1E, color="white") #XZ, 3/18/2010: pay attention to the line number of header in this file. As of today, there are 7 lines. worksheet = self.createExcelFileWithTitleAndFooter(workbook=workbook, identification=fd.identification, db=self.db, returnNumber=self.returnNumber) newrow = 7 ##################################################################### #Select All, Deselect All, Invert Selection, Add to Collection mintmap = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'showIntMap');" % mainfmName) mintmap_img = HT.Image("/images/multiple_interval_mapping1_final.jpg", name='mintmap', alt="Multiple Interval Mapping", title="Multiple Interval Mapping", style="border:none;") mintmap.append(mintmap_img) mcorr = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'compCorr');" % mainfmName) mcorr_img = HT.Image("/images/compare_correlates2_final.jpg", alt="Compare Correlates", title="Compare Correlates", style="border:none;") mcorr.append(mcorr_img) cormatrix = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'corMatrix');" % mainfmName) cormatrix_img = HT.Image("/images/correlation_matrix1_final.jpg", alt="Correlation Matrix and PCA", title="Correlation Matrix and PCA", style="border:none;") cormatrix.append(cormatrix_img) networkGraph = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'networkGraph');" % mainfmName) networkGraph_img = HT.Image("/images/network_graph1_final.jpg", name='mintmap', alt="Network Graphs", title="Network Graphs", style="border:none;") networkGraph.append(networkGraph_img) heatmap = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'heatmap');" % mainfmName) heatmap_img = HT.Image("/images/heatmap2_final.jpg", name='mintmap', alt="QTL Heat Map and Clustering", title="QTL Heatmap and Clustering", style="border:none;") heatmap.append(heatmap_img) partialCorr = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'partialCorrInput');" % mainfmName) partialCorr_img = HT.Image("/images/partial_correlation_final.jpg", name='partialCorr', alt="Partial Correlation", title="Partial Correlation", style="border:none;") partialCorr.append(partialCorr_img) addselect = HT.Href(url="#redirect", onClick="addRmvSelection('%s', document.getElementsByName('%s')[0], 'addToSelection');" % (fd.RISet, mainfmName)) addselect_img = HT.Image("/images/add_collection1_final.jpg", name="addselect", alt="Add To Collection", title="Add To Collection", style="border:none;") addselect.append(addselect_img) selectall = HT.Href(url="#redirect", onClick="checkAll(document.getElementsByName('%s')[0]);" % mainfmName) selectall_img = HT.Image("/images/select_all2_final.jpg", name="selectall", alt="Select All", title="Select All", style="border:none;") selectall.append(selectall_img) selectinvert = HT.Href(url="#redirect", onClick = "checkInvert(document.getElementsByName('%s')[0]);" % mainfmName) selectinvert_img = HT.Image("/images/invert_selection2_final.jpg", name="selectinvert", alt="Invert Selection", title="Invert Selection", style="border:none;") selectinvert.append(selectinvert_img) reset = HT.Href(url="#redirect", onClick="checkNone(document.getElementsByName('%s')[0]); return false;" % mainfmName) reset_img = HT.Image("/images/select_none2_final.jpg", alt="Select None", title="Select None", style="border:none;") reset.append(reset_img) selecttraits = HT.Input(type='button' ,name='selecttraits',value='Select Traits', onClick="checkTraits(this.form);",Class="button") selectgt = HT.Input(type='text' ,name='selectgt',value='-1.0', size=6,maxlength=10,onChange="checkNumeric(this,1.0,'-1.0','gthan','greater than filed')") selectlt = HT.Input(type='text' ,name='selectlt',value='1.0', size=6,maxlength=10,onChange="checkNumeric(this,-1.0,'1.0','lthan','less than field')") selectandor = HT.Select(name='selectandor') selectandor.append(('AND','and')) selectandor.append(('OR','or')) selectandor.selected.append('AND') #External analysis tools GCATButton = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'GCAT');" % mainfmName) GCATButton_img = HT.Image("/images/GCAT_logo_final.jpg", name="GCAT", alt="GCAT", title="GCAT", style="border:none") GCATButton.append(GCATButton_img) ODE = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'ODE');" % mainfmName) ODE_img = HT.Image("/images/ODE_logo_final.jpg", name="ode", alt="ODE", title="ODE", style="border:none") ODE.append(ODE_img) ''' #XZ, 07/07/2010: I comment out this block of code. WebGestaltScript = HT.Script(language="Javascript") WebGestaltScript.append(""" setTimeout('openWebGestalt()', 2000); function openWebGestalt(){ var thisForm = document['WebGestalt']; makeWebGestaltTree(thisForm, '%s', %d, 'edag_only.php'); } """ % (mainfmName, len(traitList))) ''' self.cursor.execute('SELECT GeneChip.GO_tree_value FROM GeneChip, ProbeFreeze, ProbeSetFreeze WHERE GeneChip.Id = ProbeFreeze.ChipId and ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and ProbeSetFreeze.Name = "%s"' % self.db.name) result = self.cursor.fetchone() if result: GO_tree_value = result[0] if GO_tree_value: WebGestalt = HT.Href(url="#redirect", onClick="databaseFunc(document.getElementsByName('%s')[0], 'GOTree');" % mainfmName) WebGestalt_img = HT.Image("/images/webgestalt_icon_final.jpg", name="webgestalt", alt="Gene Set Analysis Toolkit", title="Gene Set Analysis Toolkit", style="border:none") WebGestalt.append(WebGestalt_img) hddnWebGestalt = { 'id_list':'', 'correlation':'', 'id_value':'', 'llid_list':'', 'id_type':GO_tree_value, 'idtype':'', 'species':'', 'list':'', 'client':''} hddnWebGestalt['ref_type'] = hddnWebGestalt['id_type'] hddnWebGestalt['cat_type'] = 'GO' hddnWebGestalt['significancelevel'] = 'Top10' if self.species == 'rat': hddnWebGestalt['org'] = 'Rattus norvegicus' elif self.species == 'human': hddnWebGestalt['org'] = 'Homo sapiens' elif self.species == 'mouse': hddnWebGestalt['org'] = 'Mus musculus' else: hddnWebGestalt['org'] = '' for key in hddnWebGestalt.keys(): form.append(HT.Input(name=key, value=hddnWebGestalt[key], type='hidden')) #Create tables with options, etc pageTable = HT.TableLite(cellSpacing=0,cellPadding=0,width="100%", border=0, align="Left") containerTable = HT.TableLite(cellSpacing=0,cellPadding=0,width="90%",border=0, align="Left") if not GO_tree_value: optionsTable = HT.TableLite(cellSpacing=2, cellPadding=0,width="480", height="80", border=0, align="Left") optionsTable.append(HT.TR(HT.TD(selectall), HT.TD(reset), HT.TD(selectinvert), HT.TD(addselect), HT.TD(GCATButton), HT.TD(ODE), align="left")) optionsTable.append(HT.TR(HT.TD(" "*1,"Select"), HT.TD("Deselect"), HT.TD(" "*1,"Invert"), HT.TD(" "*3,"Add"), HT.TD("Gene Set"), HT.TD(" "*2,"GCAT"))) else: optionsTable = HT.TableLite(cellSpacing=2, cellPadding=0,width="560", height="80", border=0, align="Left") optionsTable.append(HT.TR(HT.TD(selectall), HT.TD(reset), HT.TD(selectinvert), HT.TD(addselect), HT.TD(GCATButton), HT.TD(ODE), HT.TD(WebGestalt), align="left")) optionsTable.append(HT.TR(HT.TD(" "*1,"Select"), HT.TD("Deselect"), HT.TD(" "*1,"Invert"), HT.TD(" "*3,"Add"), HT.TD("Gene Set"), HT.TD(" "*2,"GCAT"), HT.TD(" "*3, "ODE"))) containerTable.append(HT.TR(HT.TD(optionsTable))) functionTable = HT.TableLite(cellSpacing=2,cellPadding=0,width="480",height="80", border=0, align="Left") functionRow = HT.TR(HT.TD(networkGraph, width="16.7%"), HT.TD(cormatrix, width="16.7%"), HT.TD(partialCorr, width="16.7%"), HT.TD(mcorr, width="16.7%"), HT.TD(mintmap, width="16.7%"), HT.TD(heatmap), align="left") labelRow = HT.TR(HT.TD(" "*1,HT.Text("Graph")), HT.TD(" "*1,HT.Text("Matrix")), HT.TD(" "*1,HT.Text("Partial")), HT.TD(HT.Text("Compare")), HT.TD(HT.Text("QTL Map")), HT.TD(HT.Text(text="Heat Map"))) functionTable.append(functionRow, labelRow) containerTable.append(HT.TR(HT.TD(functionTable), HT.BR())) #more_options = HT.Image("/images/more_options1_final.jpg", name='more_options', alt="Expand Options", title="Expand Options", style="border:none;", Class="toggleShowHide") #containerTable.append(HT.TR(HT.TD(more_options, HT.BR(), HT.BR()))) moreOptions = HT.Input(type='button',name='options',value='More Options', onClick="",Class="toggle") fewerOptions = HT.Input(type='button',name='options',value='Fewer Options', onClick="",Class="toggle") """ if (fd.formdata.getvalue('showHideOptions') == 'less'): containerTable.append(HT.TR(HT.TD(" "), height="10"), HT.TR(HT.TD(HT.Div(fewerOptions, Class="toggleShowHide")))) containerTable.append(HT.TR(HT.TD(" "))) else: containerTable.append(HT.TR(HT.TD(" "), height="10"), HT.TR(HT.TD(HT.Div(moreOptions, Class="toggleShowHide")))) containerTable.append(HT.TR(HT.TD(" "))) """ containerTable.append(HT.TR(HT.TD(HT.Span(selecttraits,' with r > ',selectgt, ' ',selectandor, ' r < ',selectlt,Class="bd1 cbddf fs11")), style="display:none;", Class="extra_options")) chrMenu = HT.Input(type='hidden',name='chromosomes',value='all') corrHeading = HT.Paragraph('Correlation Table', Class="title") tblobj = {} if self.db.type=="Geno": containerTable.append(HT.TR(HT.TD(xlsUrl, height=60))) pageTable.append(HT.TR(HT.TD(containerTable))) tblobj['header'], worksheet = self.getTableHeaderForGeno( method=self.method, worksheet=worksheet, newrow=newrow, headingStyle=headingStyle) newrow += 1 sortby = self.getSortByValue( calculationMethod = self.method ) corrScript = HT.Script(language="Javascript") corrScript.append("var corrArray = new Array();") tblobj['body'], worksheet, corrScript = self.getTableBodyForGeno(traitList=traitList, formName=mainfmName, worksheet=worksheet, newrow=newrow, corrScript=corrScript) workbook.close() objfile = open('%s.obj' % (webqtlConfig.TMPDIR+filename), 'wb') cPickle.dump(tblobj, objfile) objfile.close() div = HT.Div(webqtlUtil.genTableObj(tblobj=tblobj, file=filename, sortby=sortby, tableID = "sortable", addIndex = "1"), corrScript, Id="sortable") pageTable.append(HT.TR(HT.TD(div))) form.append(HT.Input(name='ShowStrains',type='hidden', value =1), HT.Input(name='ShowLine',type='hidden', value =1), HT.P(), HT.P(), pageTable) TD_LR.append(corrHeading, info, form, HT.P()) self.dict['body'] = str(TD_LR) self.dict['js1'] = '' self.dict['title'] = 'Correlation' elif self.db.type=="Publish": containerTable.append(HT.TR(HT.TD(xlsUrl, height=40))) pageTable.append(HT.TR(HT.TD(containerTable))) tblobj['header'], worksheet = self.getTableHeaderForPublish(method=self.method, worksheet=worksheet, newrow=newrow, headingStyle=headingStyle) newrow += 1 sortby = self.getSortByValue( calculationMethod = self.method ) corrScript = HT.Script(language="Javascript") corrScript.append("var corrArray = new Array();") tblobj['body'], worksheet, corrScript = self.getTableBodyForPublish(traitList=traitList, formName=mainfmName, worksheet=worksheet, newrow=newrow, corrScript=corrScript, species=self.species) workbook.close() objfile = open('%s.obj' % (webqtlConfig.TMPDIR+filename), 'wb') cPickle.dump(tblobj, objfile) objfile.close() # NL, 07/27/2010. genTableObj function has been moved from templatePage.py to webqtlUtil.py; div = HT.Div(webqtlUtil.genTableObj(tblobj=tblobj, file=filename, sortby=sortby, tableID = "sortable", addIndex = "1"), corrScript, Id="sortable") pageTable.append(HT.TR(HT.TD(div))) form.append( HT.Input(name='ShowStrains',type='hidden', value =1), HT.Input(name='ShowLine',type='hidden', value =1), HT.P(), pageTable) TD_LR.append(corrHeading, info, form, HT.P()) self.dict['body'] = str(TD_LR) self.dict['js1'] = '' self.dict['title'] = 'Correlation' elif self.db.type=="ProbeSet": tblobj['header'], worksheet = self.getTableHeaderForProbeSet(method=self.method, worksheet=worksheet, newrow=newrow, headingStyle=headingStyle) newrow += 1 sortby = self.getSortByValue( calculationMethod = self.method ) corrScript = HT.Script(language="Javascript") corrScript.append("var corrArray = new Array();") tblobj['body'], worksheet, corrScript = self.getTableBodyForProbeSet(traitList=traitList, primaryTrait=myTrait, formName=mainfmName, worksheet=worksheet, newrow=newrow, corrScript=corrScript, species=self.species) workbook.close() objfile = open('%s.obj' % (webqtlConfig.TMPDIR+filename), 'wb') cPickle.dump(tblobj, objfile) objfile.close() #XZ: here is the table of traits div = HT.Div(webqtlUtil.genTableObj(tblobj=tblobj, file=filename, sortby=sortby, tableID = "sortable", addIndex = "1", hiddenColumns=["Gene ID","Homologene ID"]), corrScript, Id="sortable") #XZ, 01/12/2009: create database menu for 'Add Correlation' self.cursor.execute(""" select ProbeSetFreeze.FullName, ProbeSetFreeze.Id, Tissue.name from ProbeSetFreeze, ProbeFreeze, ProbeSetFreeze as ps2, ProbeFreeze as p2, Tissue where ps2.Id = %d and ps2.ProbeFreezeId = p2.Id and ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and (ProbeFreeze.InbredSetId = p2.InbredSetId or (ProbeFreeze.InbredSetId in (1, 3) and p2.InbredSetId in (1, 3))) and p2.ChipId = ProbeFreeze.ChipId and ps2.Id != ProbeSetFreeze.Id and ProbeFreeze.TissueId = Tissue.Id and ProbeSetFreeze.public > %d order by ProbeFreeze.TissueId, ProbeSetFreeze.CreateTime desc """ % (self.db.id, webqtlConfig.PUBLICTHRESH)) results = self.cursor.fetchall() dbCustomizer = HT.Select(results, name = "customizer") databaseMenuSub = preTissue = "" for item in results: TName, TId, TTissue = item if TTissue != preTissue: if databaseMenuSub: dbCustomizer.append(databaseMenuSub) databaseMenuSub = HT.Optgroup(label = '%s mRNA ------' % TTissue) preTissue = TTissue databaseMenuSub.append(item[:2]) if databaseMenuSub: dbCustomizer.append(databaseMenuSub) #updated by NL. Delete function generateJavaScript, move js files to dhtml.js, webqtl.js and jqueryFunction.js #variables: filename, strainIds and vals are required by getquerystring function strainIds=self.getStrainIds(species=self.species, strains=self.sample_names) var1 = HT.Input(name="filename", value=filename, type='hidden') var2 = HT.Input(name="strainIds", value=strainIds, type='hidden') var3 = HT.Input(name="vals", value=vals, type='hidden') customizerButton = HT.Input(type="button", Class="button", value="Add Correlation", onClick = "xmlhttpPost('%smain.py?FormID=AJAX_table', 'sortable', (getquerystring(this.form)))" % webqtlConfig.CGIDIR) containerTable.append(HT.TR(HT.TD(HT.Span(var1,var2,var3,customizerButton, "with", dbCustomizer, Class="bd1 cbddf fs11"), HT.BR(), HT.BR()), style="display:none;", Class="extra_options")) containerTable.append(HT.TR(HT.TD(xlsUrl, HT.BR(), HT.BR()))) pageTable.append(HT.TR(HT.TD(containerTable))) pageTable.append(HT.TR(HT.TD(div))) if self.species == 'human': heatmap = "" form.append(HT.Input(name='ShowStrains',type='hidden', value =1), HT.Input(name='ShowLine',type='hidden', value =1), info, HT.BR(), pageTable, HT.BR()) TD_LR.append(corrHeading, form, HT.P()) self.dict['body'] = str(TD_LR) self.dict['title'] = 'Correlation' # updated by NL. Delete function generateJavaScript, move js files to dhtml.js, webqtl.js and jqueryFunction.js self.dict['js1'] = '' self.dict['js2'] = 'onLoad="pageOffset()"' self.dict['layer'] = self.generateWarningLayer() else: self.dict['body'] = "" ############################# # # # CorrelationPage Functions # # # ############################# def getSortByValue(self, calculationMethod): if calculationMethod == "1": sortby = ("Sample p(r)", "up") elif calculationMethod == "2": sortby = ("Sample p(rho)", "up") elif calculationMethod == "3": #XZ: literature correlation sortby = ("Lit Corr","down") elif calculationMethod == "4": #XZ: tissue correlation sortby = ("Tissue r", "down") elif calculationMethod == "5": sortby = ("Tissue rho", "down") return sortby def generateWarningLayer(self): layerString = """ """ return layerString #XZ, 01/07/2009: In HTML code, the variable 'database' corresponds to the column 'Name' in database table. def getFileName(self, target_db_name): ### dcrowell August 2008 """Returns the name of the reference database file with which correlations are calculated. Takes argument cursor which is a cursor object of any instance of a subclass of templatePage Used by correlationPage""" query = 'SELECT Id, FullName FROM ProbeSetFreeze WHERE Name = "%s"' % target_db_name self.cursor.execute(query) result = self.cursor.fetchone() Id = result[0] FullName = result[1] FullName = FullName.replace(' ','_') FullName = FullName.replace('/','_') FileName = 'ProbeSetFreezeId_' + str(Id) + '_FullName_' + FullName + '.txt' return FileName #XZ, 01/29/2009: I modified this function. #XZ: Note that the type of StrainIds must be number, not string. def getStrainIds(self, species=None, strains=[]): StrainIds = [] for item in strains: self.cursor.execute('''SELECT Strain.Id FROM Strain, Species WHERE Strain.Name="%s" and Strain.SpeciesId=Species.Id and Species.name = "%s" ''' % (item, species)) Id = self.cursor.fetchone()[0] StrainIds.append(Id) return StrainIds #XZ, 12/12/2008: if the species is rat or human, translate the geneid to mouse geneid #XZ, 12/12/2008: if the input geneid is 'None', return 0 #XZ, 12/12/2008: if the input geneid has no corresponding mouse geneid, return 0 def translateToMouseGeneID (self, species, geneid): mouse_geneid = 0; #if input geneid is None, return 0. if not geneid: return mouse_geneid if species == 'mouse': mouse_geneid = geneid elif species == 'rat': self.cursor.execute( "SELECT mouse FROM GeneIDXRef WHERE rat=%d" % int(geneid) ) record = self.cursor.fetchone() if record: mouse_geneid = record[0] elif species == 'human': self.cursor.execute( "SELECT mouse FROM GeneIDXRef WHERE human=%d" % int(geneid) ) record = self.cursor.fetchone() if record: mouse_geneid = record[0] return mouse_geneid #XZ, 12/16/2008: the input geneid is of mouse type def checkForLitInfo(self,geneId): q = 'SELECT 1 FROM LCorrRamin3 WHERE GeneId1=%s LIMIT 1' % geneId self.cursor.execute(q) try: x = self.cursor.fetchone() if x: return True else: raise except: return False #XZ, 12/16/2008: the input geneid is of mouse type def checkSymbolForTissueCorr(self, tissueProbeSetFreezeId=0, symbol=""): q = "SELECT 1 FROM TissueProbeSetXRef WHERE TissueProbeSetFreezeId=%s and Symbol='%s' LIMIT 1" % (tissueProbeSetFreezeId,symbol) self.cursor.execute(q) try: x = self.cursor.fetchone() if x: return True else: raise except: return False def fetchAllDatabaseData(self, species, GeneId, GeneSymbol, strains, db, method, returnNumber, tissueProbeSetFreezeId): StrainIds = [] for item in strains: self.cursor.execute('''SELECT Strain.Id FROM Strain, Species WHERE Strain.Name="%s" and Strain.SpeciesId=Species.Id and Species.name = "%s" ''' % (item, species)) Id = self.cursor.fetchone()[0] StrainIds.append('%d' % Id) # break it into smaller chunks so we don't overload the MySql server nnn = len(StrainIds) / 25 if len(StrainIds) % 25: nnn += 1 oridata = [] #XZ, 09/24/2008: build one temporary table that only contains the records associated with the input GeneId tempTable = None if GeneId and db.type == "ProbeSet": if method == "3": tempTable = self.getTempLiteratureTable(species=species, input_species_geneid=GeneId, returnNumber=returnNumber) if method == "4" or method == "5": tempTable = self.getTempTissueCorrTable(primaryTraitSymbol=GeneSymbol, TissueProbeSetFreezeId=TISSUE_MOUSE_DB, method=method, returnNumber=returnNumber) for step in range(nnn): temp = [] StrainIdstep = StrainIds[step*25:min(len(StrainIds), (step+1)*25)] for item in StrainIdstep: temp.append('T%s.value' % item) if db.type == "Publish": query = "SELECT PublishXRef.Id, " dataStartPos = 1 query += string.join(temp,', ') query += ' FROM (PublishXRef, PublishFreeze)' #XZ, 03/04/2009: Xiaodong changed Data to PublishData for item in StrainIdstep: query += 'left join PublishData as T%s on T%s.Id = PublishXRef.DataId and T%s.StrainId=%s\n' %(item,item,item,item) query += "WHERE PublishXRef.InbredSetId = PublishFreeze.InbredSetId and PublishFreeze.Name = '%s'" % (db.name, ) #XZ, 09/20/2008: extract literature correlation value together with gene expression values. #XZ, 09/20/2008: notice the difference between the code in next block. elif tempTable: # we can get a little performance out of selecting our LitCorr here # but also we need to do this because we are unconcerned with probes that have no geneId associated with them # as we would not have litCorr data. if method == "3": query = "SELECT %s.Name, %s.value," % (db.type,tempTable) dataStartPos = 2 if method == "4" or method == "5": query = "SELECT %s.Name, %s.Correlation, %s.PValue," % (db.type,tempTable, tempTable) dataStartPos = 3 query += string.join(temp,', ') query += ' FROM (%s, %sXRef, %sFreeze)' % (db.type, db.type, db.type) if method == "3": query += ' LEFT JOIN %s ON %s.GeneId2=ProbeSet.GeneId ' % (tempTable,tempTable) if method == "4" or method == "5": query += ' LEFT JOIN %s ON %s.Symbol=ProbeSet.Symbol ' % (tempTable,tempTable) #XZ, 03/04/2009: Xiaodong changed Data to %sData and changed parameters from %(item,item, db.type,item,item) to %(db.type, item,item, db.type,item,item) for item in StrainIdstep: query += 'left join %sData as T%s on T%s.Id = %sXRef.DataId and T%s.StrainId=%s\n' %(db.type, item,item, db.type,item,item) if method == "3": query += "WHERE ProbeSet.GeneId IS NOT NULL AND %s.value IS NOT NULL AND %sXRef.%sFreezeId = %sFreeze.Id and %sFreeze.Name = '%s' and %s.Id = %sXRef.%sId order by %s.Id" % (tempTable,db.type, db.type, db.type, db.type, db.name, db.type, db.type, db.type, db.type) if method == "4" or method == "5": query += "WHERE ProbeSet.Symbol IS NOT NULL AND %s.Correlation IS NOT NULL AND %sXRef.%sFreezeId = %sFreeze.Id and %sFreeze.Name = '%s' and %s.Id = %sXRef.%sId order by %s.Id" % (tempTable,db.type, db.type, db.type, db.type, db.name, db.type, db.type, db.type, db.type) else: query = "SELECT %s.Name," % db.type dataStartPos = 1 query += string.join(temp,', ') query += ' FROM (%s, %sXRef, %sFreeze)' % (db.type, db.type, db.type) #XZ, 03/04/2009: Xiaodong changed Data to %sData and changed parameters from %(item,item, db.type,item,item) to %(db.type, item,item, db.type,item,item) for item in StrainIdstep: query += 'left join %sData as T%s on T%s.Id = %sXRef.DataId and T%s.StrainId=%s\n' %(db.type, item,item, db.type,item,item) query += "WHERE %sXRef.%sFreezeId = %sFreeze.Id and %sFreeze.Name = '%s' and %s.Id = %sXRef.%sId order by %s.Id" % (db.type, db.type, db.type, db.type, db.name, db.type, db.type, db.type, db.type) self.cursor.execute(query) results = self.cursor.fetchall() oridata.append(results) datasize = len(oridata[0]) traits = [] # put all of the separate data together into a huge list of lists for j in range(datasize): traitdata = list(oridata[0][j]) for i in range(1,nnn): traitdata += list(oridata[i][j][dataStartPos:]) trait = Trait(traitdata[0], traitdata[dataStartPos:]) if method == METHOD_LIT: trait.lit_corr = traitdata[1] if method in TISSUE_METHODS: trait.tissue_corr = traitdata[1] trait.p_tissue = traitdata[2] traits.append(trait) if tempTable: self.cursor.execute( 'DROP TEMPORARY TABLE %s' % tempTable ) return traits # XZ, 09/20/2008: This function creates TEMPORARY TABLE tmpTableName_2 and return its name. # XZ, 09/20/2008: It stores top literature correlation values associated with the input geneId. # XZ, 09/20/2008: Attention: In each row, the input geneId is always in column GeneId1. #XZ, 12/16/2008: the input geneid can be of mouse, rat or human type def getTempLiteratureTable(self, species, input_species_geneid, returnNumber): # according to mysql the TEMPORARY TABLE name should not have to be unique because # it is only available to the current connection. This program will be invoked via command line, but if it # were to be invoked over mod_python this could cuase problems. mod_python will keep the connection alive # in its executing threads ( i think) so there is a potential for the table not being dropped between users. #XZ, 01/29/2009: To prevent the potential risk, I generate random table names and drop the tables after use them. # the 'input_species_geneid' could be rat or human geneid, need to translate it to mouse geneid translated_mouse_geneid = self.translateToMouseGeneID (species, input_species_geneid) tmpTableName_1 = webqtlUtil.genRandStr(prefix="LITERATURE") q1 = 'CREATE TEMPORARY TABLE %s (GeneId1 int(12) unsigned, GeneId2 int(12) unsigned PRIMARY KEY, value double)' % tmpTableName_1 q2 = 'INSERT INTO %s (GeneId1, GeneId2, value) SELECT GeneId1,GeneId2,value FROM LCorrRamin3 WHERE GeneId1=%s' % (tmpTableName_1, translated_mouse_geneid) q3 = 'INSERT INTO %s (GeneId1, GeneId2, value) SELECT GeneId2,GeneId1,value FROM LCorrRamin3 WHERE GeneId2=%s AND GeneId1!=%s' % (tmpTableName_1, translated_mouse_geneid,translated_mouse_geneid) for x in [q1,q2,q3]: self.cursor.execute(x) #XZ, 09/23/2008: Just use the top records insteard of using all records tmpTableName_2 = webqtlUtil.genRandStr(prefix="TOPLITERATURE") q1 = 'CREATE TEMPORARY TABLE %s (GeneId1 int(12) unsigned, GeneId2 int(12) unsigned PRIMARY KEY, value double)' % tmpTableName_2 self.cursor.execute(q1) q2 = 'SELECT GeneId1, GeneId2, value FROM %s ORDER BY value DESC' % tmpTableName_1 self.cursor.execute(q2) result = self.cursor.fetchall() counter = 0 #this is to count how many records being inserted into table for one_row in result: mouse_geneid1, mouse_geneid2, lit_corr_alue = one_row #mouse_geneid1 has been tested before, now should test if mouse_geneid2 has corresponding geneid in other species translated_species_geneid = 0 if species == 'mouse': translated_species_geneid = mouse_geneid2 elif species == 'rat': self.cursor.execute( "SELECT rat FROM GeneIDXRef WHERE mouse=%d" % int(mouse_geneid2) ) record = self.cursor.fetchone() if record: translated_species_geneid = record[0] elif species == 'human': self.cursor.execute( "SELECT human FROM GeneIDXRef WHERE mouse=%d" % int(mouse_geneid2) ) record = self.cursor.fetchone() if record: translated_species_geneid = record[0] if translated_species_geneid: self.cursor.execute( 'INSERT INTO %s (GeneId1, GeneId2, value) VALUES (%d,%d,%f)' % (tmpTableName_2, int(input_species_geneid),int(translated_species_geneid), float(lit_corr_alue)) ) counter = counter + 1 #pay attention to the number if (counter > 2*returnNumber): break self.cursor.execute('DROP TEMPORARY TABLE %s' % tmpTableName_1) return tmpTableName_2 #XZ, 09/23/2008: In tissue correlation tables, there is no record of GeneId1 == GeneId2 #XZ, 09/24/2008: Note that the correlation value can be negative. def getTempTissueCorrTable(self, primaryTraitSymbol="", TissueProbeSetFreezeId=0, method="", returnNumber=0): def cmpTissCorrAbsoluteValue(A, B): try: if abs(A[1]) < abs(B[1]): return 1 elif abs(A[1]) == abs(B[1]): return 0 else: return -1 except: return 0 symbolCorrDict, symbolPvalueDict = self.calculateCorrOfAllTissueTrait(primaryTraitSymbol=primaryTraitSymbol, TissueProbeSetFreezeId=TISSUE_MOUSE_DB, method=method) symbolCorrList = symbolCorrDict.items() symbolCorrList.sort(cmpTissCorrAbsoluteValue) symbolCorrList = symbolCorrList[0 : 2*returnNumber] tmpTableName = webqtlUtil.genRandStr(prefix="TOPTISSUE") q1 = 'CREATE TEMPORARY TABLE %s (Symbol varchar(100) PRIMARY KEY, Correlation float, PValue float)' % tmpTableName self.cursor.execute(q1) for one_pair in symbolCorrList: one_symbol = one_pair[0] one_corr = one_pair[1] one_p_value = symbolPvalueDict[one_symbol] self.cursor.execute( "INSERT INTO %s (Symbol, Correlation, PValue) VALUES ('%s',%f,%f)" % (tmpTableName, one_symbol, float(one_corr), float(one_p_value)) ) return tmpTableName #XZ, 01/09/2009: This function was created by David Crowell. Xiaodong cleaned up and modified it. def fetchLitCorrelations(self, species, GeneId, db, returnNumber): ### Used to generate Lit Correlations when calculations are done from text file. dcrowell August 2008 """Uses getTempLiteratureTable to generate table of literatire correlations. This function then gathers that data and pairs it with the TraitID string. Takes as its arguments a formdata instance, and a database instance. Returns a dictionary of 'TraitID':'LitCorr' for the requested correlation""" tempTable = self.getTempLiteratureTable(species=species, input_species_geneid=GeneId, returnNumber=returnNumber) query = "SELECT %s.Name, %s.value" % (db.type,tempTable) query += ' FROM (%s, %sXRef, %sFreeze)' % (db.type, db.type, db.type) query += ' LEFT JOIN %s ON %s.GeneId2=ProbeSet.GeneId ' % (tempTable,tempTable) query += "WHERE ProbeSet.GeneId IS NOT NULL AND %s.value IS NOT NULL AND %sXRef.%sFreezeId = %sFreeze.Id and %sFreeze.Name = '%s' and %s.Id = %sXRef.%sId order by %s.Id" % (tempTable, db.type, db.type, db.type, db.type, db.name, db.type, db.type, db.type, db.type) self.cursor.execute(query) results = self.cursor.fetchall() litCorrDict = {} for entry in results: traitName,litcorr = entry litCorrDict[traitName] = litcorr self.cursor.execute('DROP TEMPORARY TABLE %s' % tempTable) return litCorrDict #XZ, 01/09/2009: Xiaodong created this function. def fetchTissueCorrelations(self, db, primaryTraitSymbol="", TissueProbeSetFreezeId=0, method="", returnNumber = 0): """Uses getTempTissueCorrTable to generate table of tissue correlations. This function then gathers that data and pairs it with the TraitID string. Takes as its arguments a formdata instance, and a database instance. Returns a dictionary of 'TraitID':(tissueCorr, tissuePValue) for the requested correlation""" tempTable = self.getTempTissueCorrTable(primaryTraitSymbol=primaryTraitSymbol, TissueProbeSetFreezeId=TISSUE_MOUSE_DB, method=method, returnNumber=returnNumber) query = "SELECT ProbeSet.Name, %s.Correlation, %s.PValue" % (tempTable, tempTable) query += ' FROM (ProbeSet, ProbeSetXRef, ProbeSetFreeze)' query += ' LEFT JOIN %s ON %s.Symbol=ProbeSet.Symbol ' % (tempTable,tempTable) query += "WHERE ProbeSetFreeze.Name = '%s' and ProbeSetFreeze.Id=ProbeSetXRef.ProbeSetFreezeId and ProbeSet.Id = ProbeSetXRef.ProbeSetId and ProbeSet.Symbol IS NOT NULL AND %s.Correlation IS NOT NULL" % (db.name, tempTable) self.cursor.execute(query) results = self.cursor.fetchall() tissueCorrDict = {} for entry in results: traitName, tissueCorr, tissuePValue = entry tissueCorrDict[traitName] = (tissueCorr, tissuePValue) self.cursor.execute('DROP TEMPORARY TABLE %s' % tempTable) return tissueCorrDict #XZ, 01/13/2008 def getLiteratureCorrelationByList(self, input_trait_mouse_geneid=None, species=None, traitList=None): tmpTableName = webqtlUtil.genRandStr(prefix="LITERATURE") q1 = 'CREATE TEMPORARY TABLE %s (GeneId1 int(12) unsigned, GeneId2 int(12) unsigned PRIMARY KEY, value double)' % tmpTableName q2 = 'INSERT INTO %s (GeneId1, GeneId2, value) SELECT GeneId1,GeneId2,value FROM LCorrRamin3 WHERE GeneId1=%s' % (tmpTableName, input_trait_mouse_geneid) q3 = 'INSERT INTO %s (GeneId1, GeneId2, value) SELECT GeneId2,GeneId1,value FROM LCorrRamin3 WHERE GeneId2=%s AND GeneId1!=%s' % (tmpTableName, input_trait_mouse_geneid, input_trait_mouse_geneid) for x in [q1,q2,q3]: self.cursor.execute(x) for thisTrait in traitList: try: if thisTrait.geneid: thisTrait.mouse_geneid = self.translateToMouseGeneID(species, thisTrait.geneid) else: thisTrait.mouse_geneid = 0 except: thisTrait.mouse_geneid = 0 if thisTrait.mouse_geneid and str(thisTrait.mouse_geneid).find(";") == -1: try: self.cursor.execute("SELECT value FROM %s WHERE GeneId2 = %s" % (tmpTableName, thisTrait.mouse_geneid)) result = self.cursor.fetchone() if result: thisTrait.LCorr = result[0] else: thisTrait.LCorr = None except: thisTrait.LCorr = None else: thisTrait.LCorr = None self.cursor.execute("DROP TEMPORARY TABLE %s" % tmpTableName) return traitList def get_trait(self, cached, vals): if cached: _log.info("Using the fast method because the file exists") lit_corrs = {} tissue_corrs = {} use_lit = False if self.method == METHOD_LIT: lit_corrs = self.fetchLitCorrelations(species=self.species, GeneId=self.gene_id, db=self.db, returnNumber=self.returnNumber) use_lit = True use_tissue_corr = False if self.method in TISSUE_METHODS: tissue_corrs = self.fetchTissueCorrelations(db=self.db, primaryTraitSymbol=self.trait_symbol, TissueProbeSetFreezeId=TISSUE_MOUSE_DB, method=self.method, returnNumber = self.returnNumber) use_tissue_corr = True DatabaseFileName = self.getFileName( target_db_name=self.target_db_name ) datasetFile = open(webqtlConfig.TEXTDIR+DatabaseFileName,'r') #XZ, 01/08/2009: read the first line line = datasetFile.readline() cached_sample_names = webqtlUtil.readLineCSV(line)[1:] #XZ, 01/08/2009: This step is critical. It is necessary for this new method. #XZ: The original function fetchAllDatabaseData uses all strains stored in variable _strains to #XZ: retrieve the values of each strain from database in real time. #XZ: The new method uses all strains stored in variable dataset_strains to create a new variable #XZ: _newvals. _newvals has the same length as dataset_strains. The items in _newvals is in #XZ: the same order of items in dataset_strains. The value of each item in _newvals is either #XZ: the value of correspinding strain in _vals or 'None'. new_vals = [] for name in cached_sample_names: if name in self.sample_names: new_vals.append(float(vals[self.sample_names.index(name)])) else: new_vals.append('None') nnCorr = len(new_vals) #XZ, 01/14/2009: If literature corr or tissue corr is selected, #XZ: there is no need to use parallel computing. traits = [] data_start = 1 for line in datasetFile: raw_trait = webqtlUtil.readLineCSV(line) trait = Trait.from_csv(raw_trait, data_start) trait.lit_corr = lit_corrs.get(trait.name) trait.tissue_corr, trait.p_tissue = tissue_corrs.get(trait.name, (None, None)) traits.append(trait) return traits, new_vals else: _log.info("Using the slow method for correlation") _log.info("Fetching from database") traits = self.fetchAllDatabaseData(species=self.species, GeneId=self.gene_id, GeneSymbol=self.trait_symbol, strains=self.sample_names, db=self.db, method=self.method, returnNumber=self.returnNumber, tissueProbeSetFreezeId= self.tissue_probeset_freeze_id) _log.info("Done fetching from database") totalTraits = len(traits) #XZ, 09/18/2008: total trait number return traits, vals def do_parallel_correlation(self): _log.info("Invoking parallel computing") input_line_list = datasetFile.readlines() _log.info("Read lines from the file") all_line_number = len(input_line_list) step = 1000 job_number = math.ceil( float(all_line_number)/step ) job_input_lists = [] _log.info("Configuring jobs") for job_index in range( int(job_number) ): starti = job_index*step endi = min((job_index+1)*step, all_line_number) one_job_input_list = [] for i in range( starti, endi ): one_job_input_list.append( input_line_list[i] ) job_input_lists.append( one_job_input_list ) _log.info("Creating pp servers") ppservers = () # Creates jobserver with automatically detected number of workers job_server = pp.Server(ppservers=ppservers) _log.info("Done creating servers") jobs = [] results = [] _log.info("Starting parallel computation, submitting jobs") for one_job_input_list in job_input_lists: #pay attention to modules from outside jobs.append( job_server.submit(func=compute_corr, args=(nnCorr, _newvals, one_job_input_list, self.method), depfuncs=(), modules=("utility.webqtlUtil",)) ) _log.info("Done submitting jobs") for one_job in jobs: one_result = one_job() results.append( one_result ) _log.info("Acquiring results") for one_result in results: for one_traitinfo in one_result: allcorrelations.append( one_traitinfo ) _log.info("Appending the results") datasetFile.close() totalTraits = len(allcorrelations) _log.info("Done correlating using the fast method") def correlate(self, vals): correlations = [] #XZ: Use the fast method only for probeset dataset, and this dataset must have been created. #XZ: Otherwise, use original method _log.info("Entering correlation") db_filename = self.getFileName( target_db_name=self.target_db_name ) cache_available = db_filename in os.listdir(webqtlConfig.TEXTDIR) # If the cache file exists, do a cached correlation for probeset data if self.db.type == "ProbeSet": # if self.method in [METHOD_SAMPLE_PEARSON, METHOD_SAMPLE_RANK] and cache_available: # traits = do_parallel_correlation() # # else: (traits, vals) = self.get_trait(cache_available, vals) for trait in traits: trait.calculate_correlation(vals, self.method) self.record_count = len(traits) #ZS: This isn't a good way to get this value, so I need to change it later #XZ, 3/31/2010: Theoretically, we should create one function 'comTissueCorr' #to compare each trait by their tissue corr p values. #But because the tissue corr p values are generated by permutation test, #the top ones always have p value 0. So comparing p values actually does nothing. #In addition, for the tissue data in our database, the N is always the same. #So it's safe to compare with tissue corr statistic value. #That's the same as literature corr. #if self.method in [METHOD_LIT, METHOD_TISSUE_PEARSON, METHOD_TISSUE_RANK] and self.gene_id: # traits.sort(webqtlUtil.cmpLitCorr) #else: #if self.method in TISSUE_METHODS: # sort(traits, key=lambda A: math.fabs(A.tissue_corr)) #elif self.method == METHOD_LIT: # traits.sort(traits, key=lambda A: math.fabs(A.lit_corr)) #else: traits = sortTraitCorrelations(traits, self.method) # Strip to the top N correlations traits = traits[:min(self.returnNumber, len(traits))] addLiteratureCorr = False addTissueCorr = False trait_list = [] for trait in traits: db_trait = webqtlTrait(db=self.db, name=trait.name, cursor=self.cursor) db_trait.retrieveInfo( QTL='Yes' ) db_trait.Name = trait.name db_trait.corr = trait.correlation db_trait.nOverlap = trait.overlap db_trait.corrPValue = trait.p_value # NL, 07/19/2010 # js function changed, add a new parameter rankOrder for js function 'showTissueCorrPlot' db_trait.RANK_ORDER = self.RANK_ORDERS[self.method] #XZ, 26/09/2008: Method is 4 or 5. Have fetched tissue corr, but no literature correlation yet. if self.method in TISSUE_METHODS: db_trait.tissueCorr = trait.tissue_corr db_trait.tissuePValue = trait.p_tissue addTissueCorr = True #XZ, 26/09/2008: Method is 3, Have fetched literature corr, but no tissue corr yet. elif self.method == METHOD_LIT: db_trait.LCorr = trait.lit_corr db_trait.mouse_geneid = self.translateToMouseGeneID(self.species, db_trait.geneid) addLiteratureCorr = True #XZ, 26/09/2008: Method is 1 or 2. Have NOT fetched literature corr and tissue corr yet. # Phenotype data will not have geneid, and neither will some probes # we need to handle this because we will get an attribute error else: if self.input_trait_mouse_gene_id and self.db.type=="ProbeSet": addLiteratureCorr = True if self.trait_symbol and self.db.type=="ProbeSet": addTissueCorr = True trait_list.append(db_trait) if addLiteratureCorr: trait_list = self.getLiteratureCorrelationByList(self.input_trait_mouse_gene_id, self.species, trait_list) if addTissueCorr: trait_list = self.getTissueCorrelationByList( primaryTraitSymbol = self.trait_symbol, traitList = trait_list, TissueProbeSetFreezeId = TISSUE_MOUSE_DB, method=self.method) return trait_list def calculateCorrOfAllTissueTrait(self, primaryTraitSymbol=None, TissueProbeSetFreezeId=None, method=None): symbolCorrDict = {} symbolPvalueDict = {} primaryTraitSymbolValueDict = correlationFunction.getGeneSymbolTissueValueDictForTrait(cursor=self.cursor, GeneNameLst=[primaryTraitSymbol], TissueProbeSetFreezeId=TISSUE_MOUSE_DB) primaryTraitValue = primaryTraitSymbolValueDict.values()[0] SymbolValueDict = correlationFunction.getGeneSymbolTissueValueDictForTrait(cursor=self.cursor, GeneNameLst=[], TissueProbeSetFreezeId=TISSUE_MOUSE_DB) if method in ["2","5"]: symbolCorrDict, symbolPvalueDict = correlationFunction.batchCalTissueCorr(primaryTraitValue,SymbolValueDict,method='spearman') else: symbolCorrDict, symbolPvalueDict = correlationFunction.batchCalTissueCorr(primaryTraitValue,SymbolValueDict) return (symbolCorrDict, symbolPvalueDict) #XZ, 10/13/2010 def getTissueCorrelationByList(self, primaryTraitSymbol=None, traitList=None, TissueProbeSetFreezeId=None, method=None): primaryTraitSymbolValueDict = correlationFunction.getGeneSymbolTissueValueDictForTrait(cursor=self.cursor, GeneNameLst=[primaryTraitSymbol], TissueProbeSetFreezeId=TISSUE_MOUSE_DB) if primaryTraitSymbol.lower() in primaryTraitSymbolValueDict: primaryTraitValue = primaryTraitSymbolValueDict[primaryTraitSymbol.lower()] geneSymbolList = [] for thisTrait in traitList: if hasattr(thisTrait, 'symbol'): geneSymbolList.append(thisTrait.symbol) SymbolValueDict = correlationFunction.getGeneSymbolTissueValueDictForTrait(cursor=self.cursor, GeneNameLst=geneSymbolList, TissueProbeSetFreezeId=TISSUE_MOUSE_DB) for thisTrait in traitList: if hasattr(thisTrait, 'symbol') and thisTrait.symbol and thisTrait.symbol.lower() in SymbolValueDict: oneTraitValue = SymbolValueDict[thisTrait.symbol.lower()] if method in ["2","5"]: result = correlationFunction.calZeroOrderCorrForTiss( primaryTraitValue, oneTraitValue, method='spearman' ) else: result = correlationFunction.calZeroOrderCorrForTiss( primaryTraitValue, oneTraitValue) thisTrait.tissueCorr = result[0] thisTrait.tissuePValue = result[2] else: thisTrait.tissueCorr = None thisTrait.tissuePValue = None else: for thisTrait in traitList: thisTrait.tissueCorr = None thisTrait.tissuePValue = None return traitList def getTopInfo(self, myTrait=None, method=None, db=None, target_db_name=None, returnNumber=None, methodDict=None, totalTraits=None, identification=None ): if myTrait: if method in ["1","2"]: #genetic correlation info = HT.Paragraph("Values of Record %s in the " % myTrait.getGivenName(), HT.Href(text=myTrait.db.fullname,url=webqtlConfig.INFOPAGEHREF % myTrait.db.name,target="_blank", Class="fwn"), " database were compared to all %d records in the " % self.record_count, HT.Href(text=db.fullname,url=webqtlConfig.INFOPAGEHREF % target_db_name,target="_blank", Class="fwn"), ' database. The top %d correlations ranked by the %s are displayed.' % (returnNumber,methodDict[method]), ' You can resort this list using the small arrowheads in the top row.') else: #myTrait.retrieveInfo()#need to know geneid and symbol if method == "3":#literature correlation searchDBName = "Literature Correlation" searchDBLink = "/correlationAnnotation.html#literatureCorr" else: #tissue correlation searchDBName = "Tissue Correlation" searchDBLink = "/correlationAnnotation.html#tissueCorr" info = HT.Paragraph("Your input record %s in the " % myTrait.getGivenName(), HT.Href(text=myTrait.db.fullname,url=webqtlConfig.INFOPAGEHREF % myTrait.db.name,target="_blank", Class="fwn"), " database corresponds to ", HT.Href(text='gene Id %s, and gene symbol %s' % (myTrait.geneid, myTrait.symbol), target='_blank',url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene&cmd=Retrieve&dopt=Graphics&list_uids=%s" % myTrait.geneid, Class="fs12 fwn"), '. GN ranked all genes in the ', HT.Href(text=searchDBName,url=searchDBLink,target="_blank", Class="fwn"),' database by the %s.' % methodDict[method], ' The top %d probes or probesets in the ' % returnNumber, HT.Href(text=db.fullname,url=webqtlConfig.INFOPAGEHREF % target_db_name,target="_blank", Class="fwn"), ' database corresponding to the top genes ranked by the %s are displayed.' %( methodDict[method]), ' You can resort this list using the small arrowheads in the top row.' ) elif identification: info = HT.Paragraph('Values of %s were compared to all %d traits in ' % (identification, self.record_count), HT.Href(text=db.fullname,url=webqtlConfig.INFOPAGEHREF % target_db_name,target="_blank",Class="fwn"), ' database. The TOP %d correlations ranked by the %s are displayed.' % (returnNumber,methodDict[method]), ' You can resort this list using the small arrowheads in the top row.') else: info = HT.Paragraph('Trait values were compared to all values in ', HT.Href(text=db.fullname,url=webqtlConfig.INFOPAGEHREF % target_db_name,target="_blank",Class="fwn"), ' database. The TOP %d correlations ranked by the %s are displayed.' % (returnNumber,methodDict[method]), ' You can resort this list using the small arrowheads in the top row.') if db.type=="Geno": info.append(HT.BR(),HT.BR(),'Clicking on the Locus will open the genotypes data for that locus. Click on the correlation to see a scatter plot of the trait data.') elif db.type=="Publish": info.append(HT.BR(),HT.BR(),'Clicking on the record ID will open the published phenotype data for that publication. Click on the correlation to see a scatter plot of the trait data. ') elif db.type=="ProbeSet": info.append(HT.BR(),'Click the correlation values to generate scatter plots. Select the Record ID to open the Trait Data and Analysis form. Select the symbol to open NCBI Entrez.') else: pass return info def createExcelFileWithTitleAndFooter(self, workbook=None, identification=None, db=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 # Modified by Hongqiang Li worksheet.write([1, 0], "Citations: Please see %s/reference.html" % webqtlConfig.PORTADDR, titleStyle) worksheet.write([1, 0], "Citations: Please see %s/reference.html" % webqtlConfig.PORTADDR, titleStyle) worksheet.write([2, 0], "Trait : %s" % identification, titleStyle) worksheet.write([3, 0], "Database : %s" % db.fullname, titleStyle) worksheet.write([4, 0], "Date : %s" % time.strftime("%B %d, %Y", time.gmtime()), titleStyle) worksheet.write([5, 0], "Time : %s GMT" % time.strftime("%H:%M ", time.gmtime()), titleStyle) worksheet.write([6, 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([9 + 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([10 + returnNumber, 0], "PLEASE RETAIN DATA SOURCE INFORMATION WHENEVER POSSIBLE", titleStyle) return worksheet def getTableHeaderForGeno(self, method=None, worksheet=None, newrow=None, headingStyle=None): tblobj_header = [] if method in ["1","3","4"]: tblobj_header = [[THCell(HT.TD(' ', Class="fs13 fwb ffl b1 cw cbrb"), sort=0), THCell(HT.TD('Record', HT.BR(), 'ID', HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text='Record ID', idx=1), THCell(HT.TD('Location', HT.BR(), 'Chr and Mb', HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text='Location (Chr and Mb)', idx=2), THCell(HT.TD(HT.Href( text = HT.Span('Sample',HT.BR(), 'r', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#genetic_r"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Sample r", idx=3), THCell(HT.TD('N',HT.BR(),'Cases',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="N Cases", idx=4), THCell(HT.TD(HT.Href( text = HT.Span('Sample',HT.BR(), 'p(r)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#genetic_p_r"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Sample p(r)", idx=5)]] for ncol, item in enumerate(['Record ID', 'Location (Chr, Mb)', 'Sample r', 'N Cases', 'Sample p(r)']): worksheet.write([newrow, ncol], item, headingStyle) worksheet.set_column([ncol, ncol], 2*len(item)) else: tblobj_header = [[THCell(HT.TD(' ', Class="fs13 fwb ffl b1 cw cbrb"), sort=0), THCell(HT.TD('Record', HT.BR(), 'ID', HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text='Record ID', idx=1), THCell(HT.TD('Location', HT.BR(), 'Chr and Mb', HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text='Location (Chr and Mb)', idx=2), THCell(HT.TD(HT.Href( text = HT.Span('Sample',HT.BR(), 'rho', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#genetic_rho"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Sample rho", idx=3), THCell(HT.TD('N',HT.BR(),'Cases',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="N Cases", idx=4), THCell(HT.TD(HT.Href( text = HT.Span('Sample',HT.BR(), 'p(rho)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#genetic_p_rho"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Sample p(rho)", idx=5)]] for ncol, item in enumerate(['Record ID', 'Location (Chr, Mb)', 'Sample rho', 'N Cases', 'Sample p(rho)']): worksheet.write([newrow, ncol], item, headingStyle) worksheet.set_column([ncol, ncol], 2*len(item)) return tblobj_header, worksheet def getTableBodyForGeno(self, traitList, formName=None, worksheet=None, newrow=None, corrScript=None): tblobj_body = [] for thisTrait in traitList: tr = [] trId = str(thisTrait) corrScript.append('corrArray["%s"] = {corr:%1.4f};' % (trId, thisTrait.corr)) tr.append(TDCell(HT.TD(HT.Input(type="checkbox", Class="checkbox", name="searchResult",value=trId, onClick="highlight(this)"), nowrap="on", Class="fs12 fwn ffl b1 c222"), text=trId)) tr.append(TDCell(HT.TD(HT.Href(text=thisTrait.name,url="javascript:showTrait('%s', '%s')" % (formName, thisTrait.name), Class="fs12 fwn ffl"),align="left", Class="fs12 fwn ffl b1 c222"), text=thisTrait.name, val=thisTrait.name.upper())) #XZ: trait_location_value is used for sorting trait_location_repr = '--' trait_location_value = 1000000 if thisTrait.chr and thisTrait.mb: try: trait_location_value = int(thisTrait.chr)*1000 + thisTrait.mb except: if thisTrait.chr.upper() == 'X': trait_location_value = 20*1000 + thisTrait.mb else: trait_location_value = ord(str(thisTrait.chr).upper()[0])*1000 + thisTrait.mb trait_location_repr = 'Chr%s: %.6f' % (thisTrait.chr, float(thisTrait.mb) ) tr.append(TDCell(HT.TD(trait_location_repr, Class="fs12 fwn b1 c222", nowrap="on"), trait_location_repr, trait_location_value)) repr='%3.3f' % thisTrait.corr tr.append(TDCell(HT.TD(HT.Href(text=repr, url="javascript:showCorrPlot('%s', '%s')" % (formName, thisTrait.name), Class="fs12 fwn ffl"), Class="fs12 fwn ffl b1 c222", nowrap='ON', align='right'),repr,abs(thisTrait.corr))) repr = '%d' % thisTrait.nOverlap tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222",align='right'),repr,thisTrait.nOverlap)) repr = webqtlUtil.SciFloat(thisTrait.corrPValue) tr.append(TDCell(HT.TD(repr,nowrap='ON', Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.corrPValue)) tblobj_body.append(tr) for ncol, item in enumerate([thisTrait.name, trait_location_repr, thisTrait.corr, thisTrait.nOverlap, thisTrait.corrPValue]): worksheet.write([newrow, ncol], item) newrow += 1 return tblobj_body, worksheet, corrScript def getTableHeaderForPublish(self, method=None, worksheet=None, newrow=None, headingStyle=None): tblobj_header = [] if method in ["1","3","4"]: tblobj_header = [[THCell(HT.TD(' ', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), sort=0), THCell(HT.TD('Record',HT.BR(), 'ID',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="Record ID", idx=1), THCell(HT.TD('Phenotype', HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="Phenotype", idx=2), THCell(HT.TD('Authors', HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="Authors", idx=3), THCell(HT.TD('Year', HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="Year", idx=4), THCell(HT.TD('Max',HT.BR(), 'LRS', HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="Max LRS", idx=5), THCell(HT.TD('Max LRS Location',HT.BR(),'Chr and Mb',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="Max LRS Location", idx=6), THCell(HT.TD(HT.Href( text = HT.Span('Sample',HT.BR(), 'r', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#genetic_r"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Sample r", idx=7), THCell(HT.TD('N',HT.BR(),'Cases',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="N Cases", idx=8), THCell(HT.TD(HT.Href( text = HT.Span('Sample',HT.BR(), 'p(r)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#genetic_p_r"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Sample p(r)", idx=9)]] for ncol, item in enumerate(["Record", "Phenotype", "Authors", "Year", "Pubmed Id", "Max LRS", "Max LRS Location (Chr: Mb)", "Sample r", "N Cases", "Sample p(r)"]): worksheet.write([newrow, ncol], item, headingStyle) worksheet.set_column([ncol, ncol], 2*len(item)) else: tblobj_header = [[THCell(HT.TD(' ', Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), sort=0), THCell(HT.TD('Record',HT.BR(), 'ID',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="Record ID", idx=1), THCell(HT.TD('Phenotype', HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="Phenotype", idx=2), THCell(HT.TD('Authors', HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="Authors", idx=3), THCell(HT.TD('Year', HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="Year", idx=4), THCell(HT.TD('Max',HT.BR(), 'LRS', HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="Max LRS", idx=5), THCell(HT.TD('Max LRS Location',HT.BR(),'Chr and Mb',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap="on"), text="Max LRS Location", idx=6), THCell(HT.TD(HT.Href( text = HT.Span('Sample',HT.BR(), 'rho', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#genetic_rho"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Sample rho", idx=7), THCell(HT.TD('N',HT.BR(),'Cases',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="N Cases", idx=8), THCell(HT.TD(HT.Href( text = HT.Span('Sample',HT.BR(), 'p(rho)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#genetic_p_rho"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Sample p(rho)", idx=9)]] for ncol, item in enumerate(["Record", "Phenotype", "Authors", "Year", "Pubmed Id", "Max LRS", "Max LRS Location (Chr: Mb)", "Sample rho", "N Cases", "Sample p(rho)"]): worksheet.write([newrow, ncol], item, headingStyle) worksheet.set_column([ncol, ncol], 2*len(item)) return tblobj_header, worksheet def getTableBodyForPublish(self, traitList, formName=None, worksheet=None, newrow=None, corrScript=None, species=''): tblobj_body = [] for thisTrait in traitList: tr = [] trId = str(thisTrait) corrScript.append('corrArray["%s"] = {corr:%1.4f};' % (trId, thisTrait.corr)) tr.append(TDCell(HT.TD(HT.Input(type="checkbox", Class="checkbox", name="searchResult",value=trId, onClick="highlight(this)"), nowrap="on", Class="fs12 fwn ffl b1 c222"), text=trId)) tr.append(TDCell(HT.TD(HT.Href(text=thisTrait.name,url="javascript:showTrait('%s', '%s')" % (formName, thisTrait.name), Class="fs12 fwn"), nowrap="yes",align="center", Class="fs12 fwn b1 c222"),str(thisTrait.name), thisTrait.name)) PhenotypeString = thisTrait.post_publication_description if thisTrait.confidential: if not webqtlUtil.hasAccessToConfidentialPhenotypeTrait(privilege=self.privilege, userName=self.userName, authorized_users=thisTrait.authorized_users): PhenotypeString = thisTrait.pre_publication_description tr.append(TDCell(HT.TD(PhenotypeString, Class="fs12 fwn b1 c222"), PhenotypeString, PhenotypeString.upper())) tr.append(TDCell(HT.TD(thisTrait.authors, Class="fs12 fwn b1 c222 fsI"),thisTrait.authors, thisTrait.authors.strip().upper())) try: PubMedLinkText = myear = repr = int(thisTrait.year) except: PubMedLinkText = repr = "--" myear = 0 if thisTrait.pubmed_id: PubMedLink = HT.Href(text= repr,url= webqtlConfig.PUBMEDLINK_URL % thisTrait.pubmed_id,target='_blank', Class="fs12 fwn") else: PubMedLink = repr tr.append(TDCell(HT.TD(PubMedLink, Class="fs12 fwn b1 c222", align='center'), repr, myear)) #LRS and its location LRS_score_repr = '--' LRS_score_value = 0 LRS_location_repr = '--' LRS_location_value = 1000000 LRS_flag = 1 #Max LRS and its Locus location if thisTrait.lrs and thisTrait.locus: self.cursor.execute(""" select Geno.Chr, Geno.Mb from Geno, Species where Species.Name = '%s' and Geno.Name = '%s' and Geno.SpeciesId = Species.Id """ % (species, thisTrait.locus)) result = self.cursor.fetchone() if result: if result[0] and result[1]: LRS_Chr = result[0] LRS_Mb = result[1] #XZ: LRS_location_value is used for sorting try: LRS_location_value = int(LRS_Chr)*1000 + float(LRS_Mb) except: if LRS_Chr.upper() == 'X': LRS_location_value = 20*1000 + float(LRS_Mb) else: LRS_location_value = ord(str(LRS_chr).upper()[0])*1000 + float(LRS_Mb) LRS_score_repr = '%3.1f' % thisTrait.lrs LRS_score_value = thisTrait.lrs LRS_location_repr = 'Chr%s: %.6f' % (LRS_Chr, float(LRS_Mb) ) LRS_flag = 0 #tr.append(TDCell(HT.TD(HT.Href(text=LRS_score_repr,url="javascript:showIntervalMapping('%s', '%s : %s')" % (formName, thisTrait.db.shortname, thisTrait.name), Class="fs12 fwn"), Class="fs12 fwn ffl b1 c222", align='right', nowrap="on"),LRS_score_repr, LRS_score_value)) tr.append(TDCell(HT.TD(LRS_score_repr, Class="fs12 fwn b1 c222", align='right', nowrap="on"), LRS_score_repr, LRS_score_value)) tr.append(TDCell(HT.TD(LRS_location_repr, Class="fs12 fwn b1 c222"), LRS_location_repr, LRS_location_value)) if LRS_flag: tr.append(TDCell(HT.TD(LRS_score_repr, Class="fs12 fwn b1 c222"), LRS_score_repr, LRS_score_value)) tr.append(TDCell(HT.TD(LRS_location_repr, Class="fs12 fwn b1 c222"), LRS_location_repr, LRS_location_value)) repr = '%3.4f' % thisTrait.corr tr.append(TDCell(HT.TD(HT.Href(text=repr,url="javascript:showCorrPlot('%s', '%s')" % (formName,thisTrait.name), Class="fs12 fwn"), Class="fs12 fwn b1 c222", align='right',nowrap="on"), repr, abs(thisTrait.corr))) repr = '%d' % thisTrait.nOverlap tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.nOverlap)) repr = webqtlUtil.SciFloat(thisTrait.corrPValue) tr.append(TDCell(HT.TD(repr,nowrap='ON', Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.corrPValue)) tblobj_body.append(tr) for ncol, item in enumerate([thisTrait.name, PhenotypeString, thisTrait.authors, thisTrait.year, thisTrait.pubmed_id, LRS_score_repr, LRS_location_repr, thisTrait.corr, thisTrait.nOverlap, thisTrait.corrPValue]): worksheet.write([newrow, ncol], item) newrow += 1 return tblobj_body, worksheet, corrScript def getTableHeaderForProbeSet(self, method=None, worksheet=None, newrow=None, headingStyle=None): tblobj_header = [] if method in ["1","3","4"]: tblobj_header = [[THCell(HT.TD(' ', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), sort=0), THCell(HT.TD('Record',HT.BR(), 'ID',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Record ID", idx=1), THCell(HT.TD('Gene',HT.BR(), 'ID',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Gene ID", idx=2), THCell(HT.TD('Homologene',HT.BR(), 'ID',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Homologene ID", idx=3), THCell(HT.TD('Symbol',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Symbol", idx=4), THCell(HT.TD('Description',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Description", idx=5), THCell(HT.TD('Location',HT.BR(), 'Chr and Mb', HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Location (Chr: Mb)", idx=6), THCell(HT.TD('Mean',HT.BR(),'Expr',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Mean Expr", idx=7), THCell(HT.TD('Max',HT.BR(),'LRS',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Max LRS", idx=8), THCell(HT.TD('Max LRS Location',HT.BR(),'Chr and Mb',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Max LRS Location (Chr: Mb)", idx=9), THCell(HT.TD(HT.Href( text = HT.Span('Sample',HT.BR(), 'r', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#genetic_r"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Sample r", idx=10), THCell(HT.TD('N',HT.BR(),'Cases',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="N Cases", idx=11), THCell(HT.TD(HT.Href( text = HT.Span('Sample',HT.BR(), 'p(r)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#genetic_p_r"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Sample p(r)", idx=12), THCell(HT.TD(HT.Href( text = HT.Span('Lit',HT.BR(), 'Corr', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#literatureCorr"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Lit Corr", idx=13), #XZ, 09/22/2008: tissue correlation THCell(HT.TD(HT.Href( text = HT.Span('Tissue',HT.BR(), 'r', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#tissue_r"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Tissue r", idx=14), THCell(HT.TD(HT.Href( text = HT.Span('Tissue',HT.BR(), 'p(r)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#tissue_p_r"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Tissue p(r)", idx=15)]] for ncol, item in enumerate(['Record', 'Gene ID', 'Homologene ID', 'Symbol', 'Description', 'Location (Chr: Mb)', 'Mean Expr', 'Max LRS', 'Max LRS Location (Chr: Mb)', 'Sample r', 'N Cases', 'Sample p(r)', 'Lit Corr', 'Tissue r', 'Tissue p(r)']): worksheet.write([newrow, ncol], item, headingStyle) worksheet.set_column([ncol, ncol], 2*len(item)) else: tblobj_header = [[THCell(HT.TD(' ', Class="fs13 fwb ffl b1 cw cbrb",nowrap='ON'), sort=0), THCell(HT.TD('Record',HT.BR(), 'ID',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Record ID", idx=1), THCell(HT.TD('Gene',HT.BR(), 'ID',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Gene ID", idx=2), THCell(HT.TD('Homologene',HT.BR(), 'ID',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Homologene ID", idx=3), THCell(HT.TD('Symbol',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Symbol", idx=4), THCell(HT.TD('Description',HT.BR(),HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Description", idx=5), THCell(HT.TD('Location',HT.BR(), 'Chr and Mb', HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Location (Chr: Mb)", idx=6), THCell(HT.TD('Mean',HT.BR(),'Expr',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="Mean Expr", idx=7), THCell(HT.TD('Max',HT.BR(),'LRS',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Max LRS", idx=8), THCell(HT.TD('Max LRS Location',HT.BR(),'Chr and Mb',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Max LRS Location (Chr: Mb)", idx=9), THCell(HT.TD(HT.Href( text = HT.Span('Sample',HT.BR(), 'rho', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#genetic_rho"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Sample rho", idx=10), THCell(HT.TD('N',HT.BR(),'Cases',HT.BR(), Class="fs13 fwb ffl b1 cw cbrb"), text="N Cases", idx=11), THCell(HT.TD(HT.Href( text = HT.Span('Sample',HT.BR(), 'p(rho)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#genetic_p_rho"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Sample p(rho)", idx=12), THCell(HT.TD(HT.Href( text = HT.Span('Lit',HT.BR(), 'Corr', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#literatureCorr"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Lit Corr", idx=13), #XZ, 09/22/2008: tissue correlation THCell(HT.TD(HT.Href( text = HT.Span('Tissue',HT.BR(), 'rho', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#tissue_r"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Tissue rho", idx=14), THCell(HT.TD(HT.Href( text = HT.Span('Tissue',HT.BR(), 'p(rho)', HT.Sup(' ?', style="color:#f00"),HT.BR(), Class="fs13 fwb ffl cw"), target = '_blank', url = "/correlationAnnotation.html#tissue_p_r"), Class="fs13 fwb ffl b1 cw cbrb", nowrap='ON'), text="Tissue p(rho)", idx=15)]] for ncol, item in enumerate(['Record ID', 'Gene ID', 'Homologene ID', 'Symbol', 'Description', 'Location (Chr: Mb)', 'Mean Expr', 'Max LRS', 'Max LRS Location (Chr: Mb)', 'Sample rho', 'N Cases', 'Sample p(rho)', 'Lit Corr', 'Tissue rho', 'Tissue p(rho)']): worksheet.write([newrow, ncol], item, headingStyle) worksheet.set_column([ncol, ncol], 2*len(item)) return tblobj_header, worksheet def getTableBodyForProbeSet(self, traitList=[], primaryTrait=None, formName=None, worksheet=None, newrow=None, corrScript=None, species=''): tblobj_body = [] for thisTrait in traitList: if thisTrait.symbol: pass else: thisTrait.symbol = "--" if thisTrait.geneid: symbolurl = HT.Href(text=thisTrait.symbol,target='_blank',url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene&cmd=Retrieve&dopt=Graphics&list_uids=%s" % thisTrait.geneid, Class="fs12 fwn") else: symbolurl = HT.Href(text=thisTrait.symbol,target='_blank',url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?CMD=search&DB=gene&term=%s" % thisTrait.symbol, Class="fs12 fwn") tr = [] trId = str(thisTrait) corrScript.append('corrArray["%s"] = {corr:%1.4f};' % (trId, thisTrait.corr)) #XZ, 12/08/2008: checkbox tr.append(TDCell(HT.TD(HT.Input(type="checkbox", Class="checkbox", name="searchResult",value=trId, onClick="highlight(this)"), nowrap="on", Class="fs12 fwn ffl b1 c222"), text=trId)) #XZ, 12/08/2008: probeset name tr.append(TDCell(HT.TD(HT.Href(text=thisTrait.name,url="javascript:showTrait('%s', '%s')" % (formName,thisTrait.name), Class="fs12 fwn"), Class="fs12 fwn b1 c222"), thisTrait.name, thisTrait.name.upper())) #XZ, 12/08/2008: gene id if thisTrait.geneid: tr.append(TDCell(None, thisTrait.geneid, val=999)) else: tr.append(TDCell(None, thisTrait.geneid, val=999)) #XZ, 12/08/2008: homologene id if thisTrait.homologeneid: tr.append(TDCell("", thisTrait.homologeneid, val=999)) else: tr.append(TDCell("", thisTrait.homologeneid, val=999)) #XZ, 12/08/2008: gene symbol tr.append(TDCell(HT.TD(symbolurl, Class="fs12 fwn b1 c222 fsI"),thisTrait.symbol, thisTrait.symbol.upper())) #XZ, 12/08/2008: description #XZ, 06/05/2009: Rob asked to add probe target description description_string = str(thisTrait.description).strip() target_string = str(thisTrait.probe_target_description).strip() description_display = '' if len(description_string) > 1 and description_string != 'None': description_display = description_string else: description_display = thisTrait.symbol if len(description_display) > 1 and description_display != 'N/A' and len(target_string) > 1 and target_string != 'None': description_display = description_display + '; ' + target_string.strip() tr.append(TDCell(HT.TD(description_display, Class="fs12 fwn b1 c222"), description_display, description_display)) #XZ: trait_location_value is used for sorting trait_location_repr = '--' trait_location_value = 1000000 if thisTrait.chr and thisTrait.mb: try: trait_location_value = int(thisTrait.chr)*1000 + thisTrait.mb except: if thisTrait.chr.upper() == 'X': trait_location_value = 20*1000 + thisTrait.mb else: trait_location_value = ord(str(thisTrait.chr).upper()[0])*1000 + thisTrait.mb trait_location_repr = 'Chr%s: %.6f' % (thisTrait.chr, float(thisTrait.mb) ) tr.append(TDCell(HT.TD(trait_location_repr, Class="fs12 fwn b1 c222", nowrap="on"), trait_location_repr, trait_location_value)) """ #XZ, 12/08/2008: chromosome number #XZ, 12/10/2008: use Mbvalue to sort chromosome tr.append(TDCell( HT.TD(thisTrait.chr, Class="fs12 fwn b1 c222", align='right'), thisTrait.chr, Mbvalue) ) #XZ, 12/08/2008: Rob wants 6 digit precision, and we have to deal with that the mb could be None if not thisTrait.mb: tr.append(TDCell(HT.TD(thisTrait.mb, Class="fs12 fwn b1 c222",align='right'), thisTrait.mb, Mbvalue)) else: tr.append(TDCell(HT.TD('%.6f' % thisTrait.mb, Class="fs12 fwn b1 c222", align='right'), thisTrait.mb, Mbvalue)) """ #XZ, 01/12/08: This SQL query is much faster. self.cursor.execute(""" select ProbeSetXRef.mean from ProbeSetXRef, ProbeSet where ProbeSetXRef.ProbeSetFreezeId = %d and ProbeSet.Id = ProbeSetXRef.ProbeSetId and ProbeSet.Name = '%s' """ % (thisTrait.db.id, thisTrait.name)) result = self.cursor.fetchone() if result: if result[0]: mean = result[0] else: mean=0 else: mean = 0 #XZ, 06/05/2009: It is neccessary to turn on nowrap repr = "%2.3f" % mean tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222", align='right', nowrap='ON'),repr, mean)) #LRS and its location LRS_score_repr = '--' LRS_score_value = 0 LRS_location_repr = '--' LRS_location_value = 1000000 LRS_flag = 1 #Max LRS and its Locus location if thisTrait.lrs and thisTrait.locus: self.cursor.execute(""" select Geno.Chr, Geno.Mb from Geno, Species where Species.Name = '%s' and Geno.Name = '%s' and Geno.SpeciesId = Species.Id """ % (species, thisTrait.locus)) result = self.cursor.fetchone() if result: if result[0] and result[1]: LRS_Chr = result[0] LRS_Mb = result[1] #XZ: LRS_location_value is used for sorting try: LRS_location_value = int(LRS_Chr)*1000 + float(LRS_Mb) except: if LRS_Chr.upper() == 'X': LRS_location_value = 20*1000 + float(LRS_Mb) else: LRS_location_value = ord(str(LRS_chr).upper()[0])*1000 + float(LRS_Mb) LRS_score_repr = '%3.1f' % thisTrait.lrs LRS_score_value = thisTrait.lrs LRS_location_repr = 'Chr%s: %.6f' % (LRS_Chr, float(LRS_Mb) ) LRS_flag = 0 #tr.append(TDCell(HT.TD(HT.Href(text=LRS_score_repr,url="javascript:showIntervalMapping('%s', '%s : %s')" % (formName, thisTrait.db.shortname, thisTrait.name), Class="fs12 fwn"), Class="fs12 fwn ffl b1 c222", align='right', nowrap="on"),LRS_score_repr, LRS_score_value)) tr.append(TDCell(HT.TD(LRS_score_repr, Class="fs12 fwn b1 c222", align='right', nowrap="on"), LRS_score_repr, LRS_score_value)) tr.append(TDCell(HT.TD(LRS_location_repr, Class="fs12 fwn b1 c222", nowrap="on"), LRS_location_repr, LRS_location_value)) if LRS_flag: tr.append(TDCell(HT.TD(LRS_score_repr, Class="fs12 fwn b1 c222"), LRS_score_repr, LRS_score_value)) tr.append(TDCell(HT.TD(LRS_location_repr, Class="fs12 fwn b1 c222"), LRS_location_repr, LRS_location_value)) #XZ, 12/08/2008: generic correlation repr='%3.3f' % thisTrait.corr tr.append(TDCell(HT.TD(HT.Href(text=repr, url="javascript:showCorrPlot('%s', '%s')" % (formName, thisTrait.name), Class="fs12 fwn ffl"), Class="fs12 fwn ffl b1 c222", align='right'),repr,abs(thisTrait.corr))) #XZ, 12/08/2008: number of overlaped cases repr = '%d' % thisTrait.nOverlap tr.append(TDCell(HT.TD(repr, Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.nOverlap)) #XZ, 12/08/2008: p value of genetic correlation repr = webqtlUtil.SciFloat(thisTrait.corrPValue) tr.append(TDCell(HT.TD(repr,nowrap='ON', Class="fs12 fwn ffl b1 c222", align='right'),repr,thisTrait.corrPValue)) #XZ, 12/08/2008: literature correlation LCorr = 0.0 LCorrStr = "--" if hasattr(thisTrait, 'LCorr') and thisTrait.LCorr: LCorr = thisTrait.LCorr LCorrStr = "%2.3f" % thisTrait.LCorr tr.append(TDCell(HT.TD(LCorrStr, Class="fs12 fwn b1 c222", align='right'), LCorrStr, abs(LCorr))) #XZ, 09/22/2008: tissue correlation. TCorr = 0.0 TCorrStr = "--" #XZ, 11/20/2008: need to pass two geneids: input_trait_mouse_geneid and thisTrait.mouse_geneid if hasattr(thisTrait, 'tissueCorr') and thisTrait.tissueCorr: TCorr = thisTrait.tissueCorr TCorrStr = "%2.3f" % thisTrait.tissueCorr # NL, 07/19/2010: add a new parameter rankOrder for js function 'showTissueCorrPlot' rankOrder = self.RANK_ORDERS[self.method] TCorrPlotURL = "javascript:showTissueCorrPlot('%s','%s','%s',%d)" %(formName, primaryTrait.symbol, thisTrait.symbol,rankOrder) tr.append(TDCell(HT.TD(HT.Href(text=TCorrStr, url=TCorrPlotURL, Class="fs12 fwn ff1"), Class="fs12 fwn ff1 b1 c222", align='right'), TCorrStr, abs(TCorr))) else: tr.append(TDCell(HT.TD(TCorrStr, Class="fs12 fwn b1 c222", align='right'), TCorrStr, abs(TCorr))) #XZ, 12/08/2008: p value of tissue correlation TPValue = 1.0 TPValueStr = "--" if hasattr(thisTrait, 'tissueCorr') and thisTrait.tissuePValue: #XZ, 09/22/2008: thisTrait.tissuePValue can't be used here because it could be 0 TPValue = thisTrait.tissuePValue TPValueStr = "%2.3f" % thisTrait.tissuePValue tr.append(TDCell(HT.TD(TPValueStr, Class="fs12 fwn b1 c222", align='right'), TPValueStr, TPValue)) tblobj_body.append(tr) for ncol, item in enumerate([thisTrait.name, thisTrait.geneid, thisTrait.homologeneid, thisTrait.symbol, thisTrait.description, trait_location_repr, mean, LRS_score_repr, LRS_location_repr, thisTrait.corr, thisTrait.nOverlap, thisTrait.corrPValue, LCorr, TCorr, TPValue]): worksheet.write([newrow, ncol], item) newrow += 1 return tblobj_body, worksheet, corrScript