def plotOverlayingVectors(x, vectorList, main="", xlab="", ylab="",type=None, pch='20', xname="x", ynames=None):
"""
Writes out a simple R string to plot the vectors..
"""
if not ynames:
ynames = ["y"]*len(vectorList)
maxVal=[]
minVal=[]
for v in vectorList:
maxVal.append(max(v))
minVal.append(min(v))
maxVal = max(maxVal)
minVal = min(minVal)
xmax = max(x)
xmin = min(x)
x = util.valListToStrList(x)
rstr =""
#rstr = "par(mfrow=c(1,1));\n"
rstr += xname+" <- c("+",".join(x)+");\n"
for i in range(0,len(vectorList)):
y = vectorList[i]
y = util.valListToStrList(y)
rstr += ynames[i]+" <- c("+",".join(y)+");\n"
if i!=0:
rstr += "par(new=T);\n"
rstr += 'plot('+xname+','+ynames[i]+',main="'+main+'",xlab="'+xlab+'",ylab="'+ylab+'", xlim=c('+str(xmin)+','+str(xmax)+'), ylim=c('+str(minVal)+','+str(maxVal)+'), col='+str(i+2)
if type:
rstr +=', type="'+type+'"'
if pch:
rstr +=', pch='+pch
rstr += ')\n'
return rstr
def plotVectors(x, vectorList, main="", xlab="", ylab="",type=None, xname="x", ynames=None):
"""
Writes out a simple R string to plot the vectors..
"""
if not ynames:
ynames = ["y"]*len(vectorList)
x = util.valListToStrList(x)
rstr =""
rstr = "par(mfrow=c("+str(len(vectorList))+",1));\n"
rstr += xname+" <- c("+",".join(x)+");\n"
for i in range(0,len(vectorList)):
y = util.valListToStrList(vectorList[i])
rstr += ynames[i]+" <- c("+",".join(y)+");\n"
rstr += 'plot('+xname+','+ynames[i]+',pch=20, main="'+main+'",xlab="'+xlab+'",ylab="'+ylab+'"'
if type:
rstr += ', type="'+type+'"'
rstr += ')\n'
return rstr
def _run_():
if len(sys.argv) == 1:
print __doc__
sys.exit(2)
long_options_list = ["chunkSize=", "nTrees=", "impFile=", "delim=", "missingval=", "withArrayId=", "logTransform", "phenotypeFileType=", "help", "parallel=", "parallelAll", "nodeSize=", "mem=", "round2Size=", "secondRound", "minMAF="]
try:
opts, args = getopt.getopt(sys.argv[1:], "o:d:m:a:h", long_options_list)
except:
traceback.print_exc()
print sys.exc_info()
print __doc__
sys.exit(2)
phenotypeFileType = 1
impFile = None
delim = ","
missingVal = "NA"
help = 0
withArrayIds = 1
parallel = None
logTransform = False
parallelAll = False
chunkSize = 250000
round2Size = 5000
nTrees = 15000
nodeSize = None
mem = "8g"
skipSecondRound = True
minMAF = 0.0
for opt, arg in opts:
if opt in ("-h", "--help"):
help = 1
print __doc__
elif opt in ("-a","--withArrayId"):
withArrayIds = int(arg)
elif opt in ("-o","--rFile"):
impFile = arg
elif opt in ("--phenotypeFileType"):
phenotypeFileType = int(arg)
elif opt in ("--parallel"):
parallel = arg
elif opt in ("--parallelAll"):
parallelAll = True
elif opt in ("--logTransform"):
logTransform = True
elif opt in ("--secondRound"):
skipSecondRound = False
elif opt in ("-d","--delim"):
delim = arg
elif opt in ("--chunkSize"):
chunkSize = int(arg)
elif opt in ("--round2Size"):
round2Size = int(arg)
elif opt in ("--nTrees"):
nTrees = int(arg)
elif opt in ("--nodeSize"):
nodeSize = int(arg)
elif opt in ("--mem"):
mem = arg
elif opt in ("-m","--missingval"):
missingVal = arg
elif opt in ("-m","--minMAF"):
minMAF = float(arg)
else:
if help==0:
print "Unkown option!!\n"
print __doc__
sys.exit(2)
if len(args)<3 and not parallel:
if help==0:
print "Arguments are missing!!\n"
print __doc__
sys.exit(2)
def runParallel(phenotypeIndex):
#Cluster specific parameters
phed = phenotypeData.readPhenotypeFile(phenotypeDataFile, delimiter='\t') #Get Phenotype data
phenName = phed.getPhenotypeName(phenotypeIndex)
phenName = phenName.replace("/","_div_")
phenName = phenName.replace("*","_star_")
impFileName = resultDir+"RF_"+parallel+"_"+phenName
outFileName = impFileName
shstr = """#!/bin/csh
#PBS -l walltime=120:00:00
"""
shstr += "#PBS -l mem="+mem+"\n"
shstr +="""
#PBS -q cmb
"""
shstr += "#PBS -N RF"+phenName+"_"+parallel+"\n"
shstr += "(python "+programDir+"RandomForest.py -o "+impFileName+" --chunkSize "+str(chunkSize)+" --nTrees "+str(nTrees)+" --mem "+str(mem)+" --round2Size "+str(round2Size)+""
if nodeSize:
shstr += " --nodeSize "+str(nodeSize)+" "
if logTransform:
shstr += " --logTransform "
if not skipSecondRound:
shstr += " --secondRound "
shstr += " -a "+str(withArrayIds)+" "
shstr += snpsDataFile+" "+phenotypeDataFile+" "+str(phenotypeIndex)+" "
shstr += "> "+outFileName+"_job"+".out) >& "+outFileName+"_job"+".err\n"
f = open(parallel+".sh",'w')
f.write(shstr)
f.close()
#Execute qsub script
os.system("qsub "+parallel+".sh ")
#Nested function ends
snpsDataFile = args[0]
phenotypeDataFile = args[1]
if parallel: #Running on the cluster..
if parallelAll:
phed = phenotypeData.readPhenotypeFile(phenotypeDataFile, delimiter='\t') #Get Phenotype data
for phenotypeIndex in phed.phenIds:
runParallel(phenotypeIndex)
else:
phenotypeIndex = int(args[2])
runParallel(phenotypeIndex)
return
else:
phenotypeIndex = int(args[2])
print "chunkSize:",chunkSize
print "nTrees:",nTrees
print "nodeSize:",nodeSize
print "mem:",mem
print "logTransform:",logTransform
print "round2Size:",round2Size
print "skipSecondRound:",skipSecondRound
#Loading genotype data
import dataParsers
snpsds = dataParsers.parseCSVData(snpsDataFile, format=1, deliminator=delim, missingVal=missingVal, withArrayIds=withArrayIds)
phed = phenotypeData.readPhenotypeFile(phenotypeDataFile, delimiter='\t') #Get Phenotype data
phenotype = phed.getPhenIndex(phenotypeIndex)
accIndicesToKeep = []
phenAccIndicesToKeep = []
numAcc = len(snpsds[0].accessions)
#Load phenotype file
sys.stdout.write("Removing accessions which do not have a phenotype value for "+phed.phenotypeNames[phenotype]+".")
sys.stdout.flush()
for i in range(0,len(snpsds[0].accessions)):
acc1 = snpsds[0].accessions[i]
for j in range(0,len(phed.accessions)):
acc2 = phed.accessions[j]
if acc1==acc2 and phed.phenotypeValues[j][phenotype]!='NA':
accIndicesToKeep.append(i)
phenAccIndicesToKeep.append(j)
break
#Filter accessions which do not have the phenotype value.
for snpsd in snpsds:
sys.stdout.write(".")
sys.stdout.flush()
snpsd.removeAccessionIndices(accIndicesToKeep)
print ""
print numAcc-len(accIndicesToKeep),"accessions removed, leaving",len(accIndicesToKeep),"accessions in all."
print "Filtering phenotype data."
phed.removeAccessions(phenAccIndicesToKeep) #Removing accessions that don't have genotypes or phenotype values
#Ordering accessions according to the order of accessions in the genotype file
accessionMapping = []
i = 0
for acc in snpsds[0].accessions:
if acc in phed.accessions:
accessionMapping.append((phed.accessions.index(acc),i))
i += 1
phed.orderAccessions(accessionMapping)
#Log-transforming
if logTransform:
print "Log transforming phenotype"
phed.logTransform(phenotype)
#Filtering monomorphic
print "Filtering monomorphic SNPs"
for snpsd in snpsds:
print "Removed", str(snpsd.filterMonoMorphicSnps()),"Snps"
#Remove minor allele frequencies
if minMAF!=0:
sys.stdout.write("Filterting SNPs with MAF<"+str(minMAF)+".")
for snpsd in snpsds:
sys.stdout.write(".")
sys.stdout.flush()
snpsd.filterMinMAF(minMAF)
#Converting format to 01
import snpsdata
newSnpsds = []
sys.stdout.write("Converting data format")
for snpsd in snpsds:
sys.stdout.write(".")
sys.stdout.flush()
newSnpsds.append(snpsd.getSnpsData())
print ""
snpsds = newSnpsds
#Writing files
import tempfile
if env.user=="bjarni":
tempfile.tempdir='/tmp'
(fId, phenotypeTempFile) = tempfile.mkstemp()
os.close(fId)
(fId, genotypeTempFile) = tempfile.mkstemp()
os.close(fId)
phed.writeToFile(phenotypeTempFile, [phenotype])
sys.stdout.write( "Phenotype file written\n")
sys.stdout.flush()
#Retain only the correct runchunk of data.
chromasomes = []
positions = []
snps = []
for i in range(0,len(snpsds)):
snpsd = snpsds[i]
positions += snpsd.positions
snps += snpsd.snps
chrList = [i+1]*len(snpsd.positions)
chromasomes += chrList
#Is the phenotype binary?
binary = phed.isBinary(phenotypeIndex)
import util
impFile = impFile+".imp"
rDataFile = impFile+".rData"
rFile = impFile+".r"
outRfile = rFile+".out"
errRfile = rFile+".err"
topImpFile = impFile+"_top"+str(chunkSize)+".imp"
topRDataFile = impFile+"_top.rData"
try:
os.remove(impFile) #Removing file if it already exits.
except Exception:
print "Couldn't remove",impFile
try:
os.remove(topImpFile) #Removing file if it already exits.
except Exception:
print "Couldn't remove",topImpFile
for startIndex in range(0,len(positions),chunkSize):
if startIndex+chunkSize>=len(positions):
endIndex = len(positions)
else:
endIndex = startIndex+chunkSize
#Writing genotype data to file.
tmpFile = open(genotypeTempFile,"w")
for i in range(startIndex,endIndex):
outStr =""
snp = util.valListToStrList(snps[i])
outStr += str(chromasomes[i])+","+str(positions[i])+","
outStr += ",".join(snp)
outStr += "\n"
tmpFile.write(outStr)
tmpFile.close()
rstr = _generateRScript_(genotypeTempFile, phenotypeTempFile, impFile, rDataFile, cluster=True, binary=binary, nTrees=nTrees, nodeSize=nodeSize)
f = open(rFile,'w')
f.write(rstr)
f.close()
#outRfile = rFile+"_"+str(startIndex/chunkSize)+".out"
#errRfile = rFile+"_"+str(startIndex/chunkSize)+".err"
print "Running model nr",startIndex/chunkSize,":"
cmdStr = "(R --vanilla < "+rFile+" > "+outRfile+") >& "+errRfile
sys.stdout.write(cmdStr+"\n")
sys.stdout.flush()
os.system(cmdStr)
print "Random forest output saved in", impFile
if not skipSecondRound:
#Run on the top 'chunkSize' number of hits.
#loading the R output file.
impF = open(impFile,"r")
lines=impF.readlines()
impF.close()
impList = list()
for i in range(1,len(lines)):
line = lines[i]
line.strip()
l = line.split(",")
impList.append( (float(l[2]),l[0],l[1],snps[i]) )
impList.sort()
impList.reverse()
#Writing genotype data to file.
tmpFile = open(genotypeTempFile,"w")
for i in range(0,round2Size):
outStr = ""
snp = util.valListToStrList(impList[i][3])
outStr += str(impList[i][1])+","+str(impList[i][2])+","
outStr += ",".join(snp)
outStr += "\n"
tmpFile.write(outStr)
tmpFile.close()
rstr = _generateRScript_(genotypeTempFile, phenotypeTempFile, topImpFile, topRDataFile, cluster=True, binary=binary, nTrees=nTrees, nodeSize=nodeSize)
f = open(rFile,'w')
f.write(rstr)
f.close()
print "Running randomForest on the top importance scores:"
cmdStr = "(R --vanilla < "+rFile+" > "+outRfile+") >& "+errRfile
sys.stdout.write(cmdStr+"\n")
sys.stdout.flush()
os.system(cmdStr)
def _run_():
if len(sys.argv) == 1:
print __doc__
sys.exit(2)
long_options_list = ["delim=", "missingval=", "withArrayId=", "comparisonFile=", "debug", "report", "help"]
try:
opts, args = getopt.getopt(sys.argv[1:], "o:d:m:a:brh", long_options_list)
except:
traceback.print_exc()
print sys.exc_info()
print __doc__
sys.exit(2)
inputFile = args[0]
output_fname = None
delim = ", "
missingVal = "NA"
comparisonFile = None
debug = None
report = None
help = 0
withArrayIds = 0
for opt, arg in opts:
if opt in ("-h", "--help"):
help = 1
print __doc__
elif opt in ("-a","--withArrayId"):
withArrayIds = int(arg)
elif opt in ("--comparisonFile"):
comparisonFile = arg
elif opt in ("-o",):
output_fname = arg
elif opt in ("-d","--delim"):
delim = arg
elif opt in ("-m","--missingval"):
missingVal = arg
elif opt in ("-b", "--debug"):
debug = 1
elif opt in ("-r", "--report"):
report = 1
else:
if help==0:
print "Unkown option!!\n"
print __doc__
sys.exit(2)
if not output_fname:
output_fname
if help==0:
print "Output file missing!!\n"
print __doc__
sys.exit(2)
waid1 = withArrayIds==1 or withArrayIds==2
waid2 = withArrayIds==2
import dataParsers
import snpsdata
snpsds = dataParsers.parseCSVData(inputFile, format=1, deliminator=delim, missingVal=missingVal, withArrayIds=waid1)
#Calculating Error rates
#if comparisonFile:
# snpsds2 = dataParsers.parseCSVData(comparisonFile, format=1, deliminator=delim, missingVal=missingVal, withArrayIds=waid2)
# for i in range(0,len(snpsds)):
#Compare ... and record relevant information...
#snpsds[i].compare filterBadSnps(snpsds2[i],maxError)
# pass
#Calculating NA rates..
print "Calculating NA rates"
snpsNARates = []
for i in range(0,len(snpsds)):
snpsNARates += snpsds[i].getSnpsNArates()
import util
rstr = ""
rstr += "snpsNARates <- c("+",".join(util.valListToStrList(snpsNARates))+")\n"
rstr += 'hist(snpsNARates, xlab="NA rates", ylab="SNP frequency", breaks=60)'
f = open(output_fname,"w")
f.write(rstr)
f.close()
def _run_():
if len(sys.argv) == 1:
print __doc__
sys.exit(2)
long_options_list = [
"chunkSize=", "nTrees=", "impFile=", "delim=", "missingval=",
"withArrayId=", "logTransform", "phenotypeFileType=", "help",
"parallel=", "parallelAll", "nodeSize=", "mem=", "round2Size=",
"secondRound", "minMAF="
]
try:
opts, args = getopt.getopt(sys.argv[1:], "o:d:m:a:h",
long_options_list)
except:
traceback.print_exc()
print sys.exc_info()
print __doc__
sys.exit(2)
phenotypeFileType = 1
impFile = None
delim = ","
missingVal = "NA"
help = 0
withArrayIds = 1
parallel = None
logTransform = False
parallelAll = False
chunkSize = 250000
round2Size = 5000
nTrees = 15000
nodeSize = None
mem = "8g"
skipSecondRound = True
minMAF = 0.0
for opt, arg in opts:
if opt in ("-h", "--help"):
help = 1
print __doc__
elif opt in ("-a", "--withArrayId"):
withArrayIds = int(arg)
elif opt in ("-o", "--rFile"):
impFile = arg
elif opt in ("--phenotypeFileType"):
phenotypeFileType = int(arg)
elif opt in ("--parallel"):
parallel = arg
elif opt in ("--parallelAll"):
parallelAll = True
elif opt in ("--logTransform"):
logTransform = True
elif opt in ("--secondRound"):
skipSecondRound = False
elif opt in ("-d", "--delim"):
delim = arg
elif opt in ("--chunkSize"):
chunkSize = int(arg)
elif opt in ("--round2Size"):
round2Size = int(arg)
elif opt in ("--nTrees"):
nTrees = int(arg)
elif opt in ("--nodeSize"):
nodeSize = int(arg)
elif opt in ("--mem"):
mem = arg
elif opt in ("-m", "--missingval"):
missingVal = arg
elif opt in ("-m", "--minMAF"):
minMAF = float(arg)
else:
if help == 0:
print "Unkown option!!\n"
print __doc__
sys.exit(2)
if len(args) < 3 and not parallel:
if help == 0:
print "Arguments are missing!!\n"
print __doc__
sys.exit(2)
def runParallel(phenotypeIndex):
#Cluster specific parameters
phed = phenotypeData.readPhenotypeFile(
phenotypeDataFile, delimiter='\t') #Get Phenotype data
phenName = phed.getPhenotypeName(phenotypeIndex)
phenName = phenName.replace("/", "_div_")
phenName = phenName.replace("*", "_star_")
impFileName = resultDir + "RF_" + parallel + "_" + phenName
outFileName = impFileName
shstr = """#!/bin/csh
#PBS -l walltime=50:00:00
"""
shstr += "#PBS -l mem=" + mem + "\n"
shstr += """
#PBS -q cmb
"""
shstr += "#PBS -N RF" + phenName + "_" + parallel + "\n"
shstr += "(python " + programDir + "RandomForest.py -o " + impFileName + " --chunkSize " + str(
chunkSize) + " --nTrees " + str(nTrees) + " --mem " + str(
mem) + " --round2Size " + str(round2Size) + ""
if nodeSize:
shstr += " --nodeSize " + str(nodeSize) + " "
if logTransform:
shstr += " --logTransform "
if not skipSecondRound:
shstr += " --secondRound "
shstr += " -a " + str(withArrayIds) + " "
shstr += snpsDataFile + " " + phenotypeDataFile + " " + str(
phenotypeIndex) + " "
shstr += "> " + outFileName + "_job" + ".out) >& " + outFileName + "_job" + ".err\n"
f = open(parallel + ".sh", 'w')
f.write(shstr)
f.close()
#Execute qsub script
os.system("qsub " + parallel + ".sh ")
#Nested function ends
snpsDataFile = args[0]
phenotypeDataFile = args[1]
if parallel: #Running on the cluster..
if parallelAll:
phed = phenotypeData.readPhenotypeFile(
phenotypeDataFile, delimiter='\t') #Get Phenotype data
for phenotypeIndex in phed.phenIds:
runParallel(phenotypeIndex)
else:
phenotypeIndex = int(args[2])
runParallel(phenotypeIndex)
return
else:
phenotypeIndex = int(args[2])
print "chunkSize:", chunkSize
print "nTrees:", nTrees
print "nodeSize:", nodeSize
print "mem:", mem
print "logTransform:", logTransform
print "round2Size:", round2Size
print "skipSecondRound:", skipSecondRound
#Loading genotype data
import dataParsers
snpsds = dataParsers.parseCSVData(snpsDataFile,
format=1,
deliminator=delim,
missingVal=missingVal,
withArrayIds=withArrayIds)
phed = phenotypeData.readPhenotypeFile(phenotypeDataFile,
delimiter='\t') #Get Phenotype data
phenotype = phed.getPhenIndex(phenotypeIndex)
accIndicesToKeep = []
phenAccIndicesToKeep = []
numAcc = len(snpsds[0].accessions)
#Load phenotype file
sys.stdout.write(
"Removing accessions which do not have a phenotype value for " +
phed.phenotypeNames[phenotype] + ".")
sys.stdout.flush()
for i in range(0, len(snpsds[0].accessions)):
acc1 = snpsds[0].accessions[i]
for j in range(0, len(phed.accessions)):
acc2 = phed.accessions[j]
if acc1 == acc2 and phed.phenotypeValues[j][phenotype] != 'NA':
accIndicesToKeep.append(i)
phenAccIndicesToKeep.append(j)
break
#Filter accessions which do not have the phenotype value.
for snpsd in snpsds:
sys.stdout.write(".")
sys.stdout.flush()
snpsd.removeAccessionIndices(accIndicesToKeep)
print ""
print numAcc - len(accIndicesToKeep), "accessions removed, leaving", len(
accIndicesToKeep), "accessions in all."
print "Filtering phenotype data."
phed.removeAccessions(
phenAccIndicesToKeep
) #Removing accessions that don't have genotypes or phenotype values
#Ordering accessions according to the order of accessions in the genotype file
accessionMapping = []
i = 0
for acc in snpsds[0].accessions:
if acc in phed.accessions:
accessionMapping.append((phed.accessions.index(acc), i))
i += 1
phed.orderAccessions(accessionMapping)
#Log-transforming
if logTransform:
print "Log transforming phenotype"
phed.logTransform(phenotype)
#Filtering monomorphic
print "Filtering monomorphic SNPs"
for snpsd in snpsds:
print "Removed", str(snpsd.filterMonoMorphicSnps()), "Snps"
#Remove minor allele frequencies
if minMAF != 0:
sys.stdout.write("Filterting SNPs with MAF<" + str(minMAF) + ".")
for snpsd in snpsds:
sys.stdout.write(".")
sys.stdout.flush()
snpsd.filterMinMAF(minMAF)
#Converting format to 01
import snpsdata
newSnpsds = []
sys.stdout.write("Converting data format")
for snpsd in snpsds:
sys.stdout.write(".")
sys.stdout.flush()
newSnpsds.append(snpsd.getSnpsData())
print ""
snpsds = newSnpsds
#Writing files
import tempfile
if env.user == "bjarni":
tempfile.tempdir = '/tmp'
(fId, phenotypeTempFile) = tempfile.mkstemp()
os.close(fId)
(fId, genotypeTempFile) = tempfile.mkstemp()
os.close(fId)
phed.writeToFile(phenotypeTempFile, [phenotype])
sys.stdout.write("Phenotype file written\n")
sys.stdout.flush()
#Retain only the correct runchunk of data.
chromasomes = []
positions = []
snps = []
for i in range(0, len(snpsds)):
snpsd = snpsds[i]
positions += snpsd.positions
snps += snpsd.snps
chrList = [i + 1] * len(snpsd.positions)
chromasomes += chrList
#Is the phenotype binary?
binary = phed.isBinary(phenotypeIndex)
import util
impFile = impFile + ".imp"
rDataFile = impFile + ".rData"
rFile = impFile + ".r"
outRfile = rFile + ".out"
errRfile = rFile + ".err"
topImpFile = impFile + "_top" + str(chunkSize) + ".imp"
topRDataFile = impFile + "_top.rData"
try:
os.remove(impFile) #Removing file if it already exits.
except Exception:
print "Couldn't remove", impFile
try:
os.remove(topImpFile) #Removing file if it already exits.
except Exception:
print "Couldn't remove", topImpFile
for startIndex in range(0, len(positions), chunkSize):
if startIndex + chunkSize >= len(positions):
endIndex = len(positions)
else:
endIndex = startIndex + chunkSize
#Writing genotype data to file.
tmpFile = open(genotypeTempFile, "w")
for i in range(startIndex, endIndex):
outStr = ""
snp = util.valListToStrList(snps[i])
outStr += str(chromasomes[i]) + "," + str(positions[i]) + ","
outStr += ",".join(snp)
outStr += "\n"
tmpFile.write(outStr)
tmpFile.close()
rstr = _generateRScript_(genotypeTempFile,
phenotypeTempFile,
impFile,
rDataFile,
binary=binary,
nTrees=nTrees,
nodeSize=nodeSize)
f = open(rFile, 'w')
f.write(rstr)
f.close()
#outRfile = rFile+"_"+str(startIndex/chunkSize)+".out"
#errRfile = rFile+"_"+str(startIndex/chunkSize)+".err"
print "Running model nr", startIndex / chunkSize, ":"
cmdStr = "(R --vanilla < " + rFile + " > " + outRfile + ") >& " + errRfile
sys.stdout.write(cmdStr + "\n")
sys.stdout.flush()
os.system(cmdStr)
print "Random forest output saved in", impFile
if not skipSecondRound:
#Run on the top 'chunkSize' number of hits.
#loading the R output file.
impF = open(impFile, "r")
lines = impF.readlines()
impF.close()
impList = list()
for i in range(1, len(lines)):
line = lines[i]
line.strip()
l = line.split(",")
impList.append((float(l[2]), l[0], l[1], snps[i]))
impList.sort()
impList.reverse()
#Writing genotype data to file.
tmpFile = open(genotypeTempFile, "w")
for i in range(0, round2Size):
outStr = ""
snp = util.valListToStrList(impList[i][3])
outStr += str(impList[i][1]) + "," + str(impList[i][2]) + ","
outStr += ",".join(snp)
outStr += "\n"
tmpFile.write(outStr)
tmpFile.close()
rstr = _generateRScript_(genotypeTempFile,
phenotypeTempFile,
topImpFile,
topRDataFile,
binary=binary,
nTrees=nTrees,
nodeSize=nodeSize)
f = open(rFile, 'w')
f.write(rstr)
f.close()
print "Running randomForest on the top importance scores:"
cmdStr = "(R --vanilla < " + rFile + " > " + outRfile + ") >& " + errRfile
sys.stdout.write(cmdStr + "\n")
sys.stdout.flush()
os.system(cmdStr)