def writeAnnotatedTargets(self,objective,model,annotationName,regex,iteration,oPrediction={},nPrediction={},outputFileName=None):
if outputFileName == None:
outputFileName = "Target_Report_T_%s_C_%s_M_%s_N_%s_S_%s_K_%s_I_%s.txt" % (self.resultTag,self.control,self.modelName,self.naturalObjectiveName,self.syntheticObjectiveName,self.con.controlMax,iteration)
aValue = self._annotateObjective(objective, model, annotationName, regex)
controlValues = self._condenseObjective(objective)
controlValues = self._annotateGenes(controlValues, model, annotationName, regex)
controlScores = self._controlScore(objective,oPrediction, nPrediction)
controlScores = self._annotateGenes(controlScores, model, annotationName, regex)
controlScore = self._condenseMap(controlScores,sum)
report = Report()
report.addColumnHash("Control", aValue)
report.addColumnHash("Flux", controlScore)
report.addColumnHash("Reaction Control", controlValues)
report.addColumnHash("Flux Changes", controlScores)
oName = self.resultDirectory + outputFileName
try:
writer = ReportWriter()
writer.setFile(oName)
writer.write(report)
writer.closeFile()
if self.verbose: print "Report written [%s]" % (outputFileName)
except:
if self.verbose: print "Failed to write report [%s] " % (outputFileName)
return None
def writeReport(self,ltReport,fluxModel, oPredVal,sPredVal,s2PredVal,neighborhood,iterations,fObjective,resultDir):
if self.verbose: print "Preparing report ..."
report = Report()
reactionNames = fluxModel.network.getOrderedReactionNames()
reactionMap = fluxModel.network.getReactionMap()
for reactionName in reactionNames:
reaction = reactionMap[reactionName]
equation = reaction.getEquation()
pathway = reaction.getAnnotation("Subsystem")
name = reaction.getName()#Currently sensitivity values can be too large for control factors.
report.addElement(reactionName,"name",name)
report.addElement(reactionName,"equation", equation)
report.addElement(reactionName,"Subsystem", pathway)
#--------------------
#Analysis in report
#--------------------
report.addColumnHash("Original", oPredVal)
report.addColumnHash("Synthetic", sPredVal)
report.addColumnHash("Synthetic mBio", s2PredVal)
report.extend(ltReport)
report.addColumnHash("Final Objective", fObjective)
#--------------------
#Write Report
#--------------------
if self.verbose: print "Writing report ..."
outputFileName = resultDir + "RD_" + self.resultTag + "_" + self.modelName + "_" + self.syntheticObjectiveName + "_" + str(neighborhood) + "_" + str(iterations) + "_" + strftime('%Y%m%dT%H%M%S') + ".txt"
writer = ReportWriter()
writer.setFile(outputFileName)
writer.write(report)
writer.closeFile()
if self.verbose: print "Report Written [%s]" % (outputFileName)
return report
def main_function():
parser = OptionParser()
parser.add_option("-v", "--verbose", action="store_true", dest="verbose", default=False, help="set verbose mode")
parser.add_option(
"--config",
type="string",
metavar="FILE",
dest="config",
default="redirector.config",
help="Master configuration file that provides most setting for the Flux Balanace Analysis. Extra variable settings will be ingnored. Hence the same config can be used for multiple analysis functions",
)
parser.add_option(
"-c",
"--modelConfig",
type="string",
metavar="FILE",
dest="configFileName",
default="model_config.txt",
help="Configuration file which sets model files",
)
parser.add_option(
"-n",
"--configNames",
type="string",
metavar="String",
dest="configNames",
default="Default",
help="A comma separated list of the names of configurations to use, as set out in the configuration file",
)
parser.add_option(
"-m",
"--modelname",
type="string",
metavar="String",
dest="modelName",
default="",
help="Name of model(s) from the modelconfiguration file",
)
parser.add_option(
"-b",
"--bioObjective",
type="string",
dest="bioObj",
default="Biomass",
help="Name / ID of biological objective reaction",
metavar="String",
)
parser.add_option(
"-o",
"--outputfile",
dest="outputFileName",
default=None,
help="Name of report file to be generated",
metavar="FILE",
)
parser.add_option(
"-r",
"--result_directory",
type="string",
metavar="directory",
dest="resultDirectory",
default="../../results/",
help="Directory where results are stored",
)
parser.add_option(
"--targets",
type="string",
metavar="String",
dest="targets",
default="",
help="List of valid reaction target, if left blank will be automatically filled in from metabolic network file",
)
parser.add_option(
"--report",
action="store_true",
dest="isReport",
default=False,
help="When this tag is used a report will be generated when the analysis is finished",
metavar="boolean",
)
parser.add_option("--debug", action="store_true", dest="debug", default=False, help="turn on debug mode")
parser.add_option("--gm", "--GeneMap", action="store_true", dest="useGeneMap", default=False, help="Use Gene Map")
parser.add_option(
"--section",
type="string",
metavar="String",
dest="subSections",
default="",
help="Comma separated list of sections of the model files to use",
)
# -------------------------------
# Parse options
# -------------------------------
(options, args) = parser.parse_args()
config = ReflectionConfig()
config.readfp(open("Redirector.config"))
# ---------------------------
# configure preset analysis
# ---------------------------
configNames = options.configNames.split(",")
configNames.insert(0, "Redirector Model")
for name in configNames:
config.merge(name, "Redirector", append=True)
# ----------------------------------------
# reflect options from configuration
# ----------------------------------------
config.reflect("Redirector", options)
config.load("Redirector", options.__dict__, override=False)
# -----------------------------------------
# Check and Build Storage Directories
# -----------------------------------------
dataDirectory = config.getValue("Redirector", "dataDirectory", classType="".__class__)
resultsDirectory = config.getValue("Redirector", "resultDirectory", classType="".__class__)
analysisDirectory = config.getValue("Redirector", "analysisDirectory", classType="".__class__)
if not os.path.exists(dataDirectory):
raise IOError("unable to find required data directory" % dataDirectory)
if not os.path.exists(resultsDirectory):
os.makedirs(resultsDirectory)
if not os.path.exists(analysisDirectory):
os.makedirs(analysisDirectory)
# ----------------------------
# Parse Inputs
# ----------------------------
verbose = options.verbose
modelName = options.modelName
objectiveName = options.bioObj
outputFileName = options.outputFileName
"""
#----------------------------------------------------
# Initialize and set values for tools and factories
#----------------------------------------------------
"""
naturalObjective = {objectiveName: -1.0}
if verbose:
print "Flux Balanace Analysis Version 1.6"
if verbose:
print "Model names: [%s]" % (modelName)
if verbose:
print "Parsing data files for [%s]" % (modelName)
"""
I. Parse data files and configuration settings
"""
if verbose:
print "----------------Loading Metabolic Models---------------"
modelNames = modelName.split(",")
modelFactory = ModelFactory()
config.reflect("Redirector", modelFactory)
(fluxModel, modelMatrix, reducer, geneReduction) = modelFactory.loadModel(modelNames)
model = modelMatrix
if verbose:
print "removing objectives from target set"
targets = modelMatrix.targets
if verbose:
print "Targets List Size [%s]" % len(targets)
lps = LPSolver()
predictions = lps.run(model, naturalObjective)
objectiveValue = predictions[objectiveName]
lps.clear()
if verbose:
print "Optimized Objective [%s] Value [%s]" % (objectiveName, objectiveValue)
report = fluxModel.getReport()
report.addColumnHash("Flux", predictions)
if outputFileName == None or outputFileName == "":
outputFileName = resultsDirectory + "FBA_%s_%s.txt" % (modelName, strftime("%Y%m%dT%H%M%S"))
writer = ReportWriter()
writer.setFile(outputFileName)
writer.write(report)
writer.closeFile()
if verbose:
print "Report Written [%s]" % (outputFileName)
def findBestTargetSets(targetFileObjectives,k,n):
targetdir = "../../results/"
#reportTag = "Target_Report_M_%s,_N_%s_S_%s_K_%s_I_%s.txt"
modelTag = "iAF1260,iAF1260_FattyAcids"
#naturalTag = "Biomass"
controls = ["flat","cp","T_cp_C_sense","T_cp_C_flat","T_cp_binary"]
#controls = ["flat","cp","T_cp_C_flat"]
#controlFilter = lambda x : x in [1.0,-1.0]
controlFilter = lambda x: True
#fileNameTag = targetdir + "Target_Report_T_flat_C_flat_iAF1260,iAF1260_FattyAcids_N_Biomass_S_%s_K_%s_I_%s.txt"
fileNameTag = targetdir + "Target_Report_%s_M_iAF1260,iAF1260_FattyAcids_N_Biomass_S_%s_K_%s_I_%s.txt"
sObjectiveTags = targetFileObjectives.split(",")
(targetSummaryReport,targetProductReport) = loadVariousControlTable(fileNameTag, controls, sObjectiveTags, k, n, filter = controlFilter)
targetReportFileName = "ControlSearches/Control_Target_Summary_Report_%s_%s_%s_%s_k%s_n%s.csv" % (resultTag,options.modelName,naturalObjectiveName,syntheticObjectiveName,k,n)
print "Writing target report %s" % targetReportFileName
writer = ReportWriter()
writer.setFile(targetReportFileName)
writer.write(targetSummaryReport)
writer.closeFile()
targetProductReportFileName = "ControlSearches/Control_Target_Product_Report_%s_%s_%s_%s_k%s_n%s.csv" % (controls,modelTag,naturalObjectiveName,syntheticObjectiveName,k,n)
print "Writing target product report %s" % targetProductReportFileName
writer = ReportWriter()
writer.setFile(targetProductReportFileName)
writer.write(targetProductReport)
writer.closeFile()
return None
elif options.loadFlatDep != '':
keyTag = "Row Names"
controlTag = 'control values'
productionTag = 'production'
(dependencyMaps,dReport) = loadControlTable(options.loadFlatDep, keyTag, controlTag, productionTag)
else:
(dependencyMaps,dReport) = controlDependencies(modelMatrix,resultTag,options,targetPercent,verbose=True,usePersist=usePersist)
if options.outputFileName != '':
reportFileName = "ControlSearches/Control_dependency_%s_%s_%s_%s_k%s_n%s_s%s.csv" % (resultTag,options.modelName,naturalObjectiveName,syntheticObjectiveName,k,n,str(searchDepth))
else:
reportFileName = options.outputFileName
if searchDepth != 0:
print "Writing dependency report"
writer = ReportWriter()
writer.setFile(reportFileName)
writer.write(dReport)
writer.closeFile()
'''
Build undirected graph of dependency control sets
'''
if options.makeGraph:
dgraph = buildDependencyControlGraph(dependencyMaps)
graphFileName = "ControlSearches/Dep_Graph_%s" % persistTag
if verbose: "writing undirected dependency graph [%s]" % graphFileName
dgraph.write_ps(graphFileName + ".eps")
dgraph.write(graphFileName + ".dot")
isRecord = SeqRecord(iSeq,id=id)
seqRegions.append(isRecord)
sRegionHandel = open("OligoSequenceRegions.fasta","w")
SeqIO.write(seqRegions,sRegionHandel,"fasta")
sRegionHandel.close()
seqTools = SequenceTools()
seqTools.verbose = verbose
primerReport = seqTools.findPrimers(seqData, targetMap, boundary=primerDistance, oligoSize=primerSize, searchSize=60, targetTm=primerTm)
report.extend(primerReport)
#----------------------------
# Write Report
#----------------------------
writer = ReportWriter()
writer.setFile(oligoFileName)
writer.write(report)
writer.closeFile()
#-----------------------------------------
# do comparison of recombination oligos
# to sequecing of strains
#-----------------------------------------
if mode == "sequence" or (mode == "auto" and recSeqFileName != ''):
if verbose: print "blasting sequences of recombinations"
#sequencingFeatures = seqTools.seqBlastToFeatures(blastDB, blastExe, seqResultFile, blastType = "blastn",scoreMin = 1e-5)
blastRecords = seqTools.seqBlast(blastDB, blastExe, recSeqFileName, blastType = "blastn")
if verbose: print "finsihed blasting"
