def convertCAVM(inDir, outD, REALRUN, CAVM, TCGA, MAPID=1):
bookDic = {}
sampleMaps = {}
bookDic = cgWalk(inDir, 0)
if not os.path.exists(outD):
os.system("mkdir " + outD)
if not bookDic:
print "repo has problem"
return 0
sampleMaps = collectSampleMaps(bookDic)
missingMaps = collectMissingSampleMaps(bookDic)
allMaps = sampleMaps.keys()
allMaps.extend(missingMaps.keys())
for sampleMap in allMaps:
print sampleMap
outDir = outD + sampleMap + "/"
if not os.path.exists(outDir):
os.system("mkdir " + outDir)
path = bookDic[sampleMap]['path']
"""
if string.find(os.path.abspath(path), "/inside/home/jzhu/cgDataJing/scripts/data_flatten/") ==-1:
print "ignore "+path
continue
"""
if sampleMap in missingMaps:
#construct an empty sampleMap
sMap = SampleMapNew(None, sampleMap)
#fill sMap with individual nodes, no connection
changed = checkIdsAllIn(sMap, bookDic)
#build connection
else:
name = bookDic[sampleMap]['name']
fin = open(path, 'r')
sMap = SampleMapNew(fin, name)
if not sMap.getName():
print "Fail to initiate", name
return 0
fin.close()
#cohort sampleMap json
sMapJ = {}
fin = open(bookDic[sampleMap]['path'] + ".json", 'r')
sMapJ = json.loads(fin.read())
fin.close()
#integration list
integrationList = []
rootDic = {}
clinFile = ""
clinMatrix = None
#cohort
COHORT = ""
cohortPath = string.join(
string.split(bookDic[sampleMap]['path'], "/")[0:-1],
"/") + "/cohort.json"
if os.path.exists(cohortPath):
fin = open(cohortPath, 'r')
cohortJ = json.loads(fin.read())
COHORT = cohortJ["name"]
for name in sampleMaps[sampleMap]:
obj = bookDic[name]
if obj['type'] == "clinicalMatrix":
clinFile = outDir + os.path.basename(obj['path'])
#JSON
fin = open(obj['path'] + ".json", 'r')
J = json.load(fin)
fin.close()
if COHORT:
J["cohort"] = COHORT
else:
J['cohort'] = J[':sampleMap']
J["label"] = "Phenotypes"
if CAVM:
J.pop(':sampleMap')
if J.has_key("dataSubType"):
if J.has_key(":dataSubType"):
J.pop(':dataSubType')
else:
if J.has_key(":dataSubType"):
J["dataSubType"] = J[":dataSubType"]
J.pop(':dataSubType')
fout = open(clinFile + ".json", 'w')
fout.write(json.dumps(J, indent=-1))
fout.close()
if REALRUN != 0 and REALRUN != 1:
continue
if clinMatrix != None:
print "only one clinical matrix is allowed"
sys.exit()
fin = open(obj['path'], 'U')
fout = open(clinFile, 'w')
line = fin.readline()
fout.write(line)
samples = []
for line in fin.readlines():
if MAPID:
sample = string.split(line[:-1], "\t")[-1]
else:
sample = string.split(line[:-1], "\t")[0]
if sample not in samples and sample != "":
samples.append(sample)
fout.write(sample + "\t")
if MAPID:
fout.write(
string.join(
string.split(line[:-1], "\t")[1:], "\t"))
else:
fout.write(
string.join(
string.split(line[:-1], "\t")[1:-1], "\t")
+ "\t" + sample)
fout.write("\n")
fout.close()
integrationList = copy.deepcopy(samples)
#clinicalFeature
if J.has_key(":clinicalFeature"):
cFobj = bookDic[J[":clinicalFeature"]]
outfile = outDir + os.path.basename(cFobj['path'])
os.system("cp " + cFobj['path'] + " " + outfile)
os.system("cp " + cFobj['path'] + ".json " + outfile +
".json")
#sampleMap data mapping information #cgData 1
if not CAVM:
os.system("cp " + bookDic[sampleMap]['path'] + " " +
outDir + "sampleMap")
#only expect one clinical matrix
clinMatrix = ClinicalMatrixNew(clinFile, "clinMatrix")
break
for name in sampleMaps[sampleMap]:
obj = bookDic[name]
if obj['type'] in ["genomicSegment", "mutationVector"]:
path = obj['path']
print path
outfile = outDir + os.path.basename(obj['path'])
fin = open(obj['path'] + ".json", 'r')
J = json.load(fin)
fin.close()
if COHORT:
J["cohort"] = COHORT
else:
J['cohort'] = J[':sampleMap']
if CAVM:
J.pop(':sampleMap')
if J.has_key("dataSubType"):
if J.has_key(":dataSubType"):
J.pop(':dataSubType')
else:
if J.has_key(":dataSubType"):
J["dataSubType"] = J[":dataSubType"]
J.pop(':dataSubType')
fout = open(outfile + ".json", 'w')
fout.write(json.dumps(J, indent=-1))
fout.close()
if REALRUN == 1:
fin = open(path, 'r')
fout = open(outDir + os.path.basename(path), 'w')
for line in fin.readlines():
data = string.split(line, '\t')
sample = data[0]
if rootDic.has_key(sample):
root = rootDic[sample]
else:
root = sMap.getIntegrationId(
sample, integrationList)
if not root:
root = sample
rootDic[sample] = root
fout.write(root + "\t" + string.join(data[1:], '\t'))
fin.close()
fout.close()
if obj['type'] == "genomicMatrix":
print obj['name']
#JSON
outfile = outDir + os.path.basename(obj['path'])
fin = open(obj['path'] + ".json", 'r')
J = json.load(fin)
fin.close()
if COHORT:
J["cohort"] = COHORT
else:
J['cohort'] = J[':sampleMap']
if CAVM:
J.pop(':sampleMap')
if J.has_key("dataSubType"):
if J.has_key(":dataSubType"):
J.pop(':dataSubType')
else:
if J.has_key(":dataSubType"):
J["dataSubType"] = J[":dataSubType"]
J.pop(':dataSubType')
fout = open(outfile + ".json", 'w')
fout.write(json.dumps(J, indent=-1))
fout.close()
if J.has_key('anatomical_origin'):
sMapJ['anatomical_origin'] = J['anatomical_origin']
if J.has_key('primary_disease'):
sMapJ['primary_disease'] = J['primary_disease']
if J.has_key('domain'):
sMapJ['domain'] = J['domain']
if J.has_key('sample_type'):
sMapJ['sample_type'] = J['sample_type']
if J.has_key('tags'):
sMapJ['tags'] = J['tags']
if REALRUN != 1 and REALRUN != 0:
continue
# add to clinMatrix the id mappings
mappingCol = "_GENOMIC_ID_" + obj['name']
clinMatrix.addOneColWithSameValue(mappingCol, "")
# need to find it out if there are more than one sample map to each _INTEGRATION ID
roots = {}
findDup = 0
fin = open(obj['path'], 'U')
samples = string.split(fin.readline()[:-1], "\t")[1:]
for i in range(0, len(samples)):
sample = samples[i]
if sample == "":
print name, "has bad empty sample id"
sys.exit()
if rootDic.has_key(sample):
root = rootDic[sample]
else:
root = sMap.getIntegrationId(sample, integrationList)
if not root:
root = sample
rootDic[sample] = root
genomic_Id = clinMatrix.getDATA(root, mappingCol)
if genomic_Id is None or genomic_Id == "":
clinMatrix.setDATA(root, mappingCol, sample)
else:
genomic_Id = string.split(genomic_Id, ",")
if sample not in genomic_Id:
genomic_Id.append(sample)
genomic_Id = string.join(genomic_Id, ',')
#print sample, genomic_Id
clinMatrix.setDATA(root, mappingCol, genomic_Id)
if roots.has_key(root):
roots[root].append(i)
findDup = 1
else:
roots[root] = [i]
fin.close()
if REALRUN != 1:
continue
#probemap for genomic segment
#if J.has_key(':genomicSegment'):
if J.has_key(':probeMap'):
if bookDic.has_key(J[':probeMap']):
probeMap = bookDic[J[':probeMap']]['path']
os.system("cp " + probeMap + " " + outDir +
os.path.basename(probeMap))
os.system("cp " + probeMap + ".json " + outDir +
os.path.basename(probeMap) + ".json")
#need to figure out if there are duplication in the probe ids
findDupProbe = []
process = os.popen(
"r=$(cut -f 1 " + obj['path'] +
" | more +2 | sort |uniq -c | sed -e 's/ *//' -e 's/ /\t/' | sort -n |cut -f 1 |sort -un|tail -n 1); if [ $r -ne \"1\" ]; then echo $r ; fi"
)
r = process.read()
if r:
print string.strip(r), obj['path']
process = os.popen(
"cut -f 1 " + obj['path'] +
" | more +2 | sort |uniq -c | sed -e 's/ *//' -e 's/ /\t/' | sort -n | grep -vP ^1'\t' | cut -f 2 |sort"
)
r = process.read()
list = string.split(r, "\n")
print len(list)
for probe in list:
findDupProbe.append(probe)
#genomic data no dup
fout = open(outfile, 'w')
fin = open(obj['path'], 'U')
if findDup == 0 and findDupProbe == []:
data = string.split(fin.readline()[:-1], "\t")
samples = data[1:]
fout.write(data[0])
for sample in samples:
if rootDic.has_key(sample):
root = rootDic[sample]
else:
root = sMap.getIntegrationId(
sample, integrationList)
if not root:
root = sample
rootDic[sample] = root
fout.write('\t' + root)
fout.write('\n')
if TCGA:
fin.close()
fout.close()
os.system("cat " + obj['path'] + " |sed 1d >> " +
outfile)
#os.system("more +2 "+obj['path']+" >> "+outfile)
else:
while 1:
line = fin.readline()
if line == "":
break
line = string.replace(line, "\tnan\t", "\tNA\t")
line = string.replace(line, "\tNAN\t", "\tNA\t")
line = string.replace(line, "\tNaN\t", "\tNA\t")
fout.write(line)
fin.close()
fout.close()
#genomic data with dup
else:
print "genomic with dup", obj['path']
data = string.split(fin.readline()[:-1], "\t")
fout.write(data[0])
for root in roots:
fout.write('\t' + root)
fout.write('\n')
dupDic = {}
while 1:
duplist = []
line = fin.readline()[:-1]
if line == "":
break
data = string.split(line, "\t")
if data[0] not in findDupProbe:
fout.write(data[0])
else:
if data[0] not in dupDic:
dupDic[data[0]] = []
values = data[1:]
for root in roots:
if len(roots[root]) != 1:
total = "NA"
n = 0
for i in roots[root]:
if values[i] in ["nan", "NAN", "NaN"]:
pass
else:
try:
float(values[i])
if total == "NA":
total = float(values[i])
else:
total = total + float(
values[i])
n = n + 1
except:
pass
if total != "NA":
average = str(total / n)
else:
average = "NA"
else:
if values[roots[root][0]] in [
"nan", "NAN", "NaN"
]:
average = "NA"
else:
try:
float(values[roots[root][0]])
average = values[roots[root][0]]
except:
average = "NA"
if data[0] not in findDupProbe:
fout.write('\t' + average)
else:
duplist.append(average)
if data[0] not in findDupProbe:
fout.write('\n')
else:
dupDic[data[0]].append(duplist[:])
if dupDic != {}:
for probe in dupDic:
fout.write(probe)
k = len(dupDic[probe][0])
valList = []
nList = []
for i in range(0, k):
valList.append("NA")
nList.append(0)
for list in dupDic[probe]:
for i in range(0, k):
try:
float(list[i])
if valList[i] == "NA":
valList[i] = float(list[i])
else:
valList[i] = valList[i] + float(
list[i])
nList[i] = nList[i] + 1
except:
pass
for i in range(0, k):
try:
float(valList[i])
fout.write(
"\t" +
str(float(valList[i]) / nList[i]))
except:
fout.write("\tNA")
fout.write("\n")
fin.close()
fout.close()
#final clinical matrix output
if REALRUN == 0 or REALRUN == 1:
fout = open(clinFile, 'w')
clinMatrix.store(fout)
#sampleMap json #cgData1
if not CAVM:
outfile = outDir + "sampleMap.json"
fout = open(outfile, 'w')
fout.write(json.dumps(sMapJ, indent=-1))
fout.close()
#cohort json cp or create
cohortPath = string.join(
string.split(bookDic[sampleMap]['path'], "/")[0:-1],
"/") + "/cohort.json"
if os.path.exists(cohortPath):
os.system("cp " + cohortPath + " " + outDir)
else:
outfile = outDir + "cohort.json"
fout = open(outfile, 'w')
cohortJ = {}
cohortJ["type"] = "cohort"
cohortJ["name"] = sampleMap
fout.write(json.dumps(cohortJ, indent=-1))
fout.close()
def convertCAVM (inDir, outD ,REALRUN, CAVM, TCGA, MAPID=1):
bookDic={}
sampleMaps={}
bookDic=cgWalk(inDir,0)
if not os.path.exists (outD):
os.system("mkdir "+outD)
if not bookDic :
print "repo has problem"
return 0
sampleMaps = collectSampleMaps(bookDic)
missingMaps= collectMissingSampleMaps(bookDic)
allMaps = sampleMaps.keys()
allMaps.extend(missingMaps.keys())
for sampleMap in allMaps:
print sampleMap
outDir = outD + sampleMap+"/"
if not os.path.exists (outDir):
os.system("mkdir "+outDir)
path = bookDic[sampleMap]['path']
"""
if string.find(os.path.abspath(path), "/inside/home/jzhu/cgDataJing/scripts/data_flatten/") ==-1:
print "ignore "+path
continue
"""
if sampleMap in missingMaps:
#construct an empty sampleMap
sMap = SampleMapNew(None,sampleMap)
#fill sMap with individual nodes, no connection
changed = checkIdsAllIn(sMap, bookDic)
#build connection
else:
name = bookDic[sampleMap]['name']
fin = open(path,'r')
sMap = SampleMapNew(fin,name)
if not sMap.getName():
print "Fail to initiate", name
return 0
fin.close()
#cohort sampleMap json
sMapJ={}
fin = open(bookDic[sampleMap]['path']+".json",'r')
sMapJ = json.loads(fin.read())
fin.close()
#integration list
integrationList =[]
rootDic={}
clinFile =""
clinMatrix = None
#cohort
COHORT =""
cohortPath= string.join(string.split(bookDic[sampleMap]['path'],"/")[0:-1],"/")+"/cohort.json"
if os.path.exists(cohortPath):
fin = open (cohortPath,'r')
cohortJ= json.loads(fin.read())
COHORT = cohortJ["name"]
for name in sampleMaps[sampleMap]:
obj=bookDic[name]
if obj['type']=="clinicalMatrix":
clinFile = outDir +os.path.basename(obj['path'])
#JSON
fin = open (obj['path']+".json",'r')
J=json.load(fin)
fin.close()
if COHORT :
J["cohort"]=COHORT
else:
J['cohort']=J[':sampleMap']
J["label"]="Phenotypes"
if CAVM:
J.pop(':sampleMap')
if J.has_key("dataSubType"):
if J.has_key(":dataSubType"):
J.pop(':dataSubType')
else:
if J.has_key(":dataSubType"):
J["dataSubType"]=J[":dataSubType"]
J.pop(':dataSubType')
fout=open(clinFile+".json",'w')
fout.write(json.dumps (J, indent=-1))
fout.close()
if REALRUN != 0 and REALRUN !=1:
continue
if clinMatrix != None:
print "only one clinical matrix is allowed"
sys.exit()
fin = open(obj['path'],'U')
fout = open(clinFile,'w')
line = fin.readline()
fout.write(line)
samples =[]
for line in fin.readlines():
if MAPID:
sample =string.split(line[:-1],"\t")[-1]
else:
sample =string.split(line[:-1],"\t")[0]
if sample not in samples and sample !="":
samples.append(sample)
fout.write(sample+"\t")
if MAPID:
fout.write(string.join(string.split(line[:-1],"\t")[1:],"\t"))
else:
fout.write(string.join(string.split(line[:-1],"\t")[1:-1],"\t")+"\t"+sample)
fout.write("\n")
fout.close()
integrationList = copy.deepcopy(samples)
#clinicalFeature
if J.has_key(":clinicalFeature"):
cFobj= bookDic[J[":clinicalFeature"]]
outfile = outDir +os.path.basename(cFobj['path'])
os.system("cp "+cFobj['path']+" "+outfile)
os.system("cp "+cFobj['path']+".json "+outfile+".json")
#sampleMap data mapping information #cgData 1
if not CAVM:
os.system("cp "+ bookDic[sampleMap]['path'] +" "+outDir+"sampleMap")
#only expect one clinical matrix
clinMatrix= ClinicalMatrixNew(clinFile, "clinMatrix")
break
for name in sampleMaps[sampleMap]:
obj=bookDic[name]
if obj['type'] in ["genomicSegment","mutationVector"]:
path= obj['path']
print path
outfile = outDir +os.path.basename(obj['path'])
fin = open (obj['path']+".json",'r')
J=json.load(fin)
fin.close()
if COHORT :
J["cohort"]=COHORT
else:
J['cohort']=J[':sampleMap']
if CAVM:
J.pop(':sampleMap')
if J.has_key("dataSubType"):
if J.has_key(":dataSubType"):
J.pop(':dataSubType')
else:
if J.has_key(":dataSubType"):
J["dataSubType"]=J[":dataSubType"]
J.pop(':dataSubType')
fout=open(outfile+".json",'w')
fout.write(json.dumps (J, indent=-1))
fout.close()
if REALRUN ==1 :
fin =open(path,'r')
fout =open(outDir+os.path.basename(path),'w')
for line in fin.readlines():
data = string.split(line,'\t')
sample =data[0]
if rootDic.has_key(sample):
root = rootDic[sample]
else:
root = sMap.getIntegrationId(sample,integrationList)
if not root:
root = sample
rootDic[sample]=root
fout.write(root+"\t"+string.join(data[1:],'\t'))
fin.close()
fout.close()
if obj['type']=="genomicMatrix":
print obj['name']
#JSON
outfile = outDir +os.path.basename(obj['path'])
fin = open (obj['path']+".json",'r')
J=json.load(fin)
fin.close()
if COHORT :
J["cohort"]=COHORT
else:
J['cohort']=J[':sampleMap']
if CAVM:
J.pop(':sampleMap')
if J.has_key("dataSubType"):
if J.has_key(":dataSubType"):
J.pop(':dataSubType')
else:
if J.has_key(":dataSubType"):
J["dataSubType"]=J[":dataSubType"]
J.pop(':dataSubType')
fout=open(outfile+".json",'w')
fout.write(json.dumps (J, indent=-1))
fout.close()
if J.has_key('anatomical_origin'):
sMapJ['anatomical_origin']=J['anatomical_origin']
if J.has_key('primary_disease'):
sMapJ['primary_disease']=J['primary_disease']
if J.has_key('domain'):
sMapJ['domain']=J['domain']
if J.has_key('sample_type'):
sMapJ['sample_type']=J['sample_type']
if J.has_key('tags'):
sMapJ['tags']=J['tags']
if REALRUN != 1 and REALRUN !=0:
continue
# add to clinMatrix the id mappings
mappingCol= "_GENOMIC_ID_"+obj['name']
clinMatrix.addOneColWithSameValue(mappingCol,"")
# need to find it out if there are more than one sample map to each _INTEGRATION ID
roots={}
findDup=0
fin =open(obj['path'],'U')
samples =string.split(fin.readline()[:-1],"\t")[1:]
for i in range(0,len(samples)):
sample = samples[i]
if sample =="":
print name, "has bad empty sample id"
sys.exit()
if rootDic.has_key(sample):
root = rootDic[sample]
else:
root = sMap.getIntegrationId(sample,integrationList)
if not root:
root = sample
rootDic[sample]=root
genomic_Id= clinMatrix.getDATA(root, mappingCol)
if genomic_Id is None or genomic_Id =="":
clinMatrix.setDATA(root, mappingCol,sample)
else:
genomic_Id = string.split(genomic_Id,",")
if sample not in genomic_Id:
genomic_Id.append(sample)
genomic_Id= string.join(genomic_Id,',')
#print sample, genomic_Id
clinMatrix.setDATA(root, mappingCol,genomic_Id)
if roots.has_key(root):
roots[root].append(i)
findDup=1
else:
roots[root]=[i]
fin.close()
if REALRUN != 1:
continue
#probemap for genomic segment
#if J.has_key(':genomicSegment'):
if J.has_key(':probeMap'):
if bookDic.has_key(J[':probeMap']):
probeMap = bookDic[J[':probeMap']]['path']
os.system("cp "+probeMap+" "+outDir+os.path.basename(probeMap))
os.system("cp "+probeMap+".json "+outDir+os.path.basename(probeMap)+".json")
#need to figure out if there are duplication in the probe ids
findDupProbe=[]
process = os.popen("r=$(cut -f 1 "+obj['path']+" | more +2 | sort |uniq -c | sed -e 's/ *//' -e 's/ /\t/' | sort -n |cut -f 1 |sort -un|tail -n 1); if [ $r -ne \"1\" ]; then echo $r ; fi")
r = process.read()
if r:
print string.strip(r), obj['path']
process = os.popen("cut -f 1 "+obj['path']+" | more +2 | sort |uniq -c | sed -e 's/ *//' -e 's/ /\t/' | sort -n | grep -vP ^1'\t' | cut -f 2 |sort")
r = process.read()
list = string.split(r,"\n")
print len(list)
for probe in list:
findDupProbe.append(probe)
#genomic data no dup
fout=open(outfile ,'w')
fin =open(obj['path'],'U')
if findDup ==0 and findDupProbe ==[]:
data =string.split(fin.readline()[:-1],"\t")
samples= data[1:]
fout.write(data[0])
for sample in samples:
if rootDic.has_key(sample):
root = rootDic[sample]
else:
root = sMap.getIntegrationId(sample,integrationList)
if not root:
root = sample
rootDic[sample]=root
fout.write('\t'+root)
fout.write('\n')
if TCGA:
fin.close()
fout.close()
os.system("cat "+obj['path']+" |sed 1d >> "+outfile)
#os.system("more +2 "+obj['path']+" >> "+outfile)
else:
while 1:
line = fin.readline()
if line =="":
break
line = string.replace(line,"\tnan\t","\tNA\t")
line = string.replace(line,"\tNAN\t","\tNA\t")
line = string.replace(line,"\tNaN\t","\tNA\t")
fout.write(line)
fin.close()
fout.close()
#genomic data with dup
else:
print "genomic with dup",obj['path']
data =string.split(fin.readline()[:-1],"\t")
fout.write(data[0])
for root in roots:
fout.write('\t'+root)
fout.write('\n')
dupDic ={}
while 1:
duplist=[]
line = fin.readline()[:-1]
if line =="":
break
data = string.split(line,"\t")
if data[0] not in findDupProbe:
fout.write(data[0])
else:
if data[0] not in dupDic:
dupDic[data[0]]=[]
values =data[1:]
for root in roots:
if len(roots[root])!=1:
total="NA"
n=0
for i in roots[root]:
if values[i] in ["nan","NAN","NaN"]:
pass
else:
try:
float(values[i])
if total=="NA":
total = float(values[i])
else:
total = total +float(values[i])
n=n+1
except:
pass
if total != "NA":
average = str(total / n)
else:
average ="NA"
else:
if values[roots[root][0]] in ["nan","NAN","NaN"]:
average="NA"
else:
try:
float(values[roots[root][0]])
average = values[roots[root][0]]
except:
average="NA"
if data[0] not in findDupProbe:
fout.write('\t'+average)
else:
duplist.append(average)
if data[0] not in findDupProbe:
fout.write('\n')
else:
dupDic[data[0]].append(duplist[:])
if dupDic!={}:
for probe in dupDic:
fout.write(probe)
k = len (dupDic[probe][0])
valList=[]
nList=[]
for i in range (0,k):
valList.append("NA")
nList.append(0)
for list in dupDic[probe]:
for i in range (0,k):
try:
float(list[i])
if valList [i]=="NA":
valList[i]=float(list[i])
else:
valList[i] =valList[i] +float(list[i])
nList[i]=nList[i]+1
except:
pass
for i in range (0,k):
try:
float(valList[i])
fout.write("\t"+str(float(valList[i])/nList[i]))
except:
fout.write("\tNA")
fout.write("\n")
fin.close()
fout.close()
#final clinical matrix output
if REALRUN == 0 or REALRUN ==1:
fout= open(clinFile,'w')
clinMatrix.store(fout)
#sampleMap json #cgData1
if not CAVM:
outfile = outDir +"sampleMap.json"
fout=open(outfile, 'w')
fout.write(json.dumps(sMapJ,indent=-1))
fout.close()
#cohort json cp or create
cohortPath= string.join(string.split(bookDic[sampleMap]['path'],"/")[0:-1],"/")+"/cohort.json"
if os.path.exists(cohortPath):
os.system("cp " + cohortPath +" " + outDir)
else:
outfile = outDir+"cohort.json"
fout=open(outfile,'w')
cohortJ={}
cohortJ["type"]="cohort"
cohortJ["name"]= sampleMap
fout.write(json.dumps(cohortJ,indent=-1))
fout.close()
