def colorNodes(folderName, mummerPath, sourceFilename, contigFilename, readsetFilename):
print "colorNodes"
lenDic = IORobot.obtainLength(folderName, sourceFilename + ".fasta")
print lenDic
thresForShort = 15000
shortList = []
longList = []
for eachitem in lenDic:
if lenDic[eachitem] > thresForShort:
longList.append(eachitem)
else:
shortList.append(eachitem)
IORobot.putListToFileO(folderName, sourceFilename + ".fasta", contigFilename, longList)
IORobot.putListToFileO(folderName, sourceFilename + ".fasta", readsetFilename, shortList)
def colorNodes(folderName, mummerPath,sourceFilename, contigFilename, readsetFilename):
print "colorNodes"
lenDic = IORobot.obtainLength(folderName, sourceFilename+".fasta")
print lenDic
thresForShort = 15000
shortList = []
longList = []
for eachitem in lenDic:
if lenDic[eachitem] > thresForShort:
longList.append(eachitem)
else:
shortList.append(eachitem)
IORobot.putListToFileO(folderName, sourceFilename+".fasta", contigFilename, longList)
IORobot.putListToFileO(folderName, sourceFilename+".fasta", readsetFilename, shortList)
def evaluateCoverage(dataList, lenDic, readLenDic, folderName, mummerLink, continueFilter):
myCountDic = {}
for eachitem in lenDic:
myCountDic[eachitem] = 0
dataList.sort(key=itemgetter(-1))
ctkk, ctbase = 0, 0
toAddBackDic = copy.deepcopy(readLenDic)
for key, items in groupby(dataList, itemgetter(-1)):
maxMatch = -1
bestname = ""
for eachitem in items:
ct = eachitem[6] / 100.0 * eachitem[4]
if ct > maxMatch:
maxMatch = ct
bestname = eachitem[-2]
myCountDic[bestname] += readLenDic[key]
ctkk = ctkk + 1
ctbase = ctbase + readLenDic[key]
toAddBackDic[key] = -1
cttot = 0
for eachitem in readLenDic:
cttot = cttot + readLenDic[eachitem]
print "Missed coverage ", (cttot - ctbase) / (4.7 * pow(10, 6))
print "percentage miss read", (len(readLenDic) - ctkk) / (1.0 * len(readLenDic))
toAddReadList = []
for eachitem in toAddBackDic:
if toAddBackDic[eachitem] >= 0:
toAddReadList.append(eachitem)
"""
This part need the most parallelism because it is most intense with -l 10
split V, workerList V , combine
"""
if continueFilter:
numberOfFiles = 20
IORobot.putListToFileO(folderName, "raw_reads.fasta", "selected_raw", toAddReadList)
bindir = os.path.abspath(os.path.dirname(sys.argv[0]))
command = (
bindir
+ "/finisherSCCoreLib/fasta-splitter.pl --n-parts "
+ str(numberOfFiles)
+ " "
+ folderName
+ "selected_raw.fasta"
)
os.system(command)
workerList = []
for dummyI in range(1, numberOfFiles + 1):
indexOfMum = ""
if dummyI < 10:
indexOfMum = "0" + str(dummyI)
else:
indexOfMum = str(dummyI)
outputName, referenceName, queryName, specialName = (
"outAbunRefine" + indexOfMum,
"improved3.fasta",
"selected_raw.part-" + indexOfMum + ".fasta",
"abunMissOut" + indexOfMum,
)
workerList.append([outputName, referenceName, queryName, specialName])
alignerRobot.useMummerAlignBatch(
mummerLink, folderName, workerList, houseKeeper.globalParallel, specialForRaw=True, refinedVersion=True
)
alignerRobot.combineMultipleCoorMum(True, mummerLink, folderName, "outAbunRefine", "abunMissOut", numberOfFiles)
for i in range(len(myCountDic)):
eachitem = "Segkk" + str(i)
print eachitem, myCountDic[eachitem] / (1.0 * lenDic[eachitem])
myCountDic[eachitem] = myCountDic[eachitem] / (1.0 * lenDic[eachitem])
return myCountDic
def resolvingTandem(
folderName, mummerPath, contigReadGraph, contigFilename, readsetFilename, optTypeFileHeader, repeatSpec
):
print "resolvingTandem"
"""
Input : repeat info
Output : count, join.
Algorithm:
1. Find loops
2. Form repeat
3. Form chain of repeat copies back to back
4. Align reads
5. Calculate extra bases beyond flanking region
6. Calculate count
7. Join the contigs
"""
# 0 ) Load all the data
thres = 5
G = graphLib.seqGraph(0)
G.loadFromFile(folderName, contigReadGraph)
lenDicCC = IORobot.obtainLength(folderName, contigFilename + "_Double.fasta")
N1 = len(lenDicCC)
maxDuplicate = 10
repeatTempFilename = "tandemRepeatTemplate.fasta"
mummerFile = "myTandemRepeatTemplate"
myContigsDic = IORobot.loadContigsFromFile(folderName, readsetFilename + "_Double.fasta")
lenDicRR = IORobot.obtainLength(folderName, readsetFilename + "_Double.fasta")
header = optTypeFileHeader + "RR"
dataListRR = alignerRobot.extractMumData(folderName, header + "Out")
dataListRR = abunHouseKeeper.filterData(dataListRR, lenDicRR)
dataListRRDic = {}
for eachitem in dataListRR:
if eachitem[2] < thres:
dataListRRDic[eachitem[-2] + ";" + eachitem[-1]] = eachitem[4]
header = optTypeFileHeader + "CR"
lenDicCC = IORobot.obtainLength(folderName, contigFilename + "_Double.fasta")
lenDicCR = dict(lenDicCC.items() + lenDicRR.items())
dataListCR = alignerRobot.extractMumData(folderName, header + "Out")
dataListCR = abunHouseKeeper.filterData(dataListCR, lenDicCR)
dataListCRDic = {}
for eachitem in dataListCR:
if eachitem[2] < thres:
dataListCRDic[eachitem[-2] + ";" + eachitem[-1]] = eachitem[4]
print dataListCRDic
json_data = open(folderName + repeatSpec, "r")
loadData = json.load(json_data)
contigsTmp = IORobot.loadContigsFromFile(folderName, contigFilename + "_Double.fasta")
readTmp = IORobot.loadContigsFromFile(folderName, readsetFilename + "_Double.fasta")
happyTandemList = {}
for eachrepProfile in loadData:
# 1)
startContig = eachrepProfile[-1][0][0]
isTerminate, returnPathList = DFSwithPath(G, G.graphNodesList[startContig], [startContig], N1, False)
# 2)
if isTerminate:
v = returnPathList[-1]
i = 0
tandemPath = []
while i < len(returnPathList):
if returnPathList[i] == v:
tandemPath = returnPathList[i:]
i = len(returnPathList)
i = i + 1
print returnPathList
print tandemPath
# 3) [fix it when have time later ; to just use graph; bug at the min thing]
repeatContent = ""
for kk in range(len(tandemPath[0:-1])):
eachitem = tandemPath[kk] - N1
nextitem = tandemPath[kk + 1] - N1
readName = "Read" + str(eachitem / 2) + "_"
nextReadName = "Read" + str(nextitem / 2) + "_"
if eachitem % 2 == 0:
readName = readName + "p"
elif eachitem % 2 == 1:
readName = readName + "d"
if nextitem % 2 == 0:
nextReadName = nextReadName + "p"
elif nextitem % 2 == 1:
nextReadName = nextReadName + "d"
overlap = dataListRRDic[readName + ";" + nextReadName]
print overlap
repeatContent = repeatContent + myContigsDic[readName][0:-overlap]
print "len(repeatContent)", len(repeatContent)
fout = open(folderName + repeatTempFilename, "w")
fout.write(">RepeatSegment\n")
repeatContentLarge = ""
for i in range(maxDuplicate):
fout.write(repeatContent)
repeatContentLarge = repeatContentLarge + repeatContent
fout.close()
# 4)
repeatReadList = eachrepProfile[1]
myList = []
for eachitem in repeatReadList:
readName = "Read" + str((eachitem - N1) / 2) + "_"
if eachitem % 2 == 0:
readName = readName + "p"
elif eachitem % 2 == 1:
readName = readName + "d"
myList.append(readName)
IORobot.putListToFileO(folderName, readsetFilename + "_Double.fasta", "toAlignReads", myList)
if True:
alignerRobot.useMummerAlign(mummerPath, folderName, mummerFile, repeatTempFilename, "toAlignReads.fasta")
dataList = alignerRobot.extractMumData(folderName, mummerFile + "Out")
# 5)
totalBasesMatch = 0
lrepeat = len(repeatContent)
c = findCoverageFromRawData(folderName)
# print "dataList[0]", dataList[0]
dataList.sort(key=itemgetter(-1))
for key, values in groupby(dataList, itemgetter(-1)):
maxValue = -1
for eachsub in values:
if eachsub[5] > maxValue:
maxValue = eachsub[5]
# print key, maxValue
totalBasesMatch = totalBasesMatch + maxValue
print c, lrepeat, totalBasesMatch
ct = totalBasesMatch * 1.0 / (c * lrepeat)
print "BIG NUMBER of THE DAY: ", ct
# 6)
# a) find the starting point
startContig = eachrepProfile[-1][0][0]
firstRead = eachrepProfile[-1][0][1] - N1
contigName = "Contig" + str(startContig / 2)
if startContig % 2 == 0:
contigName = contigName + "_p"
elif startContig % 2 == 1:
contigName = contigName + "_d"
readName = "Read" + str(firstRead / 2)
if firstRead % 2 == 0:
readName = readName + "_p"
elif firstRead % 2 == 1:
readName = readName + "_d"
overlapFirst = dataListCRDic[contigName + ";" + readName]
tmpCombine = contigsTmp[contigName][0:-overlapFirst] + readTmp[readName]
f1 = open(folderName + "firstOverlap.fasta", "w")
f1.write(">combined\n")
f1.write(tmpCombine)
f1.close()
if True:
alignerRobot.useMummerAlign(
mummerPath, folderName, "myFirstOverlap", repeatTempFilename, "firstOverlap.fasta"
)
dataList = alignerRobot.extractMumData(folderName, "myFirstOverlap" + "Out")
dataList.sort(key=itemgetter(0))
maxVal = -1
maxItm = []
for eachi in dataList:
if eachi[5] > maxVal:
maxVal = eachi[5]
maxItm = eachi
print maxItm
if len(maxItm) > 0:
repeatStart = maxItm[0]
contigEnd = maxItm[2]
else:
repeatStart = 0
contigEnd = -1
# b) format return : prepare the repeat template
print "ct*lrepeat", int(repeatStart + ct * lrepeat)
print "repeatStart", repeatStart
happyTandemList[contigName] = repeatContentLarge[repeatStart : int(repeatStart + ct * lrepeat)]
contigsTmp[contigName] = tmpCombine[0:contigEnd]
print "len(contigsTmp[contigName])", len(contigsTmp[contigName])
print "len(happyTandemList[contigName])", len(happyTandemList[contigName])
# 7) Combine all the repeat information and do the join
leaderList = [i for i in range(len(contigsTmp))]
for eachrepProfile in loadData:
startContig = eachrepProfile[-1][0][0]
endContig = eachrepProfile[-1][-1][-1]
leaderContig = leaderList[startContig]
leaderName = parseIDToName(leaderContig)
endName = parseIDToName(endContig)
startName = parseIDToName(startContig)
contigsTmp[leaderName] = contigsTmp[leaderName] + happyTandemList[startName]
if endContig != leaderContig:
contigsTmp[leaderName] = contigsTmp[leaderName] + contigsTmp[endName]
contigsTmp[endName] = ""
leaderList[endContig] = leaderContig
leaderAgg = [[] for i in range(len(leaderList))]
for i in range(len(leaderList)):
leaderAgg[leaderList[i]].append(i)
checkingList = [False for i in range(N1)]
fout = open(folderName + "tademResolved.fasta", "w")
counter = 0
for eachcontig in contigsTmp:
id = abunHouseKeeper.parseEdgeNameToID(eachcontig, "C")
if checkingList[id / 2] == False:
fout.write(">Segkk" + str(counter) + "\n")
fout.write(contigsTmp[eachcontig])
counter = counter + 1
for eachkk in leaderAgg[leaderList[id]]:
checkingList[eachkk / 2] = True
fout.close()
def resolvingTandem(folderName, mummerPath, contigReadGraph,contigFilename, readsetFilename, optTypeFileHeader, repeatSpec):
print "resolvingTandem"
'''
Input : repeat info
Output : count, join.
Algorithm:
1. Find loops
2. Form repeat
3. Form chain of repeat copies back to back
4. Align reads
5. Calculate extra bases beyond flanking region
6. Calculate count
7. Join the contigs
'''
# 0 ) Load all the data
thres = 5
G = graphLib.seqGraph(0)
G.loadFromFile(folderName, contigReadGraph)
lenDicCC = IORobot.obtainLength(folderName, contigFilename+"_Double.fasta")
N1 = len(lenDicCC)
maxDuplicate = 10
repeatTempFilename = "tandemRepeatTemplate.fasta"
mummerFile = "myTandemRepeatTemplate"
myContigsDic = IORobot.loadContigsFromFile(folderName, readsetFilename+"_Double.fasta")
lenDicRR = IORobot.obtainLength(folderName, readsetFilename + "_Double.fasta")
header = optTypeFileHeader + "RR"
dataListRR = alignerRobot.extractMumData(folderName, header + "Out")
dataListRR = abunHouseKeeper.filterData(dataListRR, lenDicRR)
dataListRRDic = {}
for eachitem in dataListRR:
if eachitem[2] < thres:
dataListRRDic[eachitem[-2] +";"+eachitem[-1]] = eachitem[4]
header = optTypeFileHeader + "CR"
lenDicCC = IORobot.obtainLength(folderName, contigFilename + "_Double.fasta")
lenDicCR = dict(lenDicCC.items() + lenDicRR.items())
dataListCR = alignerRobot.extractMumData(folderName, header + "Out")
dataListCR = abunHouseKeeper.filterData(dataListCR, lenDicCR)
dataListCRDic = {}
for eachitem in dataListCR:
if eachitem[2] < thres:
dataListCRDic[eachitem[-2] +";"+eachitem[-1]] = eachitem[4]
print dataListCRDic
json_data = open(folderName + repeatSpec, 'r')
loadData = json.load(json_data)
contigsTmp = IORobot.loadContigsFromFile(folderName, contigFilename+"_Double.fasta")
readTmp = IORobot.loadContigsFromFile(folderName, readsetFilename + "_Double.fasta")
happyTandemList = {}
for eachrepProfile in loadData:
# 1)
startContig = eachrepProfile[-1][0][0]
isTerminate, returnPathList = DFSwithPath(G, G.graphNodesList[startContig], [startContig], N1, False)
# 2)
if isTerminate:
v = returnPathList[-1]
i =0
tandemPath = []
while i < len(returnPathList):
if returnPathList[i] == v:
tandemPath = returnPathList[i:]
i = len(returnPathList)
i = i +1
print returnPathList
print tandemPath
# 3) [fix it when have time later ; to just use graph; bug at the min thing]
repeatContent = ""
for kk in range(len(tandemPath[0:-1])):
eachitem = tandemPath[kk]- N1
nextitem = tandemPath[kk+1] - N1
readName = "Read" + str(eachitem/2) + "_"
nextReadName = "Read" + str(nextitem/2) + "_"
if eachitem %2 ==0 :
readName = readName + "p"
elif eachitem %2 ==1:
readName = readName + "d"
if nextitem %2 ==0 :
nextReadName = nextReadName + "p"
elif nextitem %2 ==1:
nextReadName = nextReadName + "d"
overlap = dataListRRDic[readName + ";" + nextReadName]
print overlap
repeatContent = repeatContent + myContigsDic[readName][0:-overlap]
print "len(repeatContent)", len(repeatContent)
fout = open(folderName + repeatTempFilename, 'w')
fout.write(">RepeatSegment\n")
repeatContentLarge = ""
for i in range(maxDuplicate):
fout.write(repeatContent)
repeatContentLarge= repeatContentLarge + repeatContent
fout.close()
# 4)
repeatReadList = eachrepProfile[1]
myList= []
for eachitem in repeatReadList:
readName = "Read" + str((eachitem- N1)/2) + "_"
if eachitem %2 ==0 :
readName = readName + "p"
elif eachitem %2 ==1:
readName = readName + "d"
myList.append(readName)
IORobot.putListToFileO(folderName, readsetFilename+"_Double.fasta", "toAlignReads", myList)
if True:
alignerRobot.useMummerAlign(mummerPath, folderName,mummerFile , repeatTempFilename, "toAlignReads.fasta")
dataList = alignerRobot.extractMumData(folderName, mummerFile+"Out")
# 5)
totalBasesMatch = 0
lrepeat = len(repeatContent)
c = findCoverageFromRawData(folderName)
# print "dataList[0]", dataList[0]
dataList.sort(key = itemgetter(-1))
for key, values in groupby(dataList,itemgetter(-1)):
maxValue = -1
for eachsub in values:
if eachsub[5] > maxValue:
maxValue = eachsub[5]
#print key, maxValue
totalBasesMatch = totalBasesMatch + maxValue
print c, lrepeat, totalBasesMatch
ct = totalBasesMatch*1.0/(c*lrepeat)
print "BIG NUMBER of THE DAY: ", ct
# 6)
# a) find the starting point
startContig = eachrepProfile[-1][0][0]
firstRead = eachrepProfile[-1][0][1]-N1
contigName = "Contig"+ str(startContig/2)
if startContig %2 == 0:
contigName = contigName + "_p"
elif startContig%2 ==1:
contigName = contigName + "_d"
readName = "Read"+ str(firstRead/2)
if firstRead %2 == 0:
readName = readName + "_p"
elif firstRead%2 ==1:
readName = readName + "_d"
overlapFirst = dataListCRDic[contigName+";"+readName]
tmpCombine = contigsTmp[contigName][0:-overlapFirst] + readTmp[readName]
f1 = open(folderName + "firstOverlap.fasta", 'w')
f1.write(">combined\n")
f1.write(tmpCombine)
f1.close()
if True:
alignerRobot.useMummerAlign(mummerPath, folderName,"myFirstOverlap" , repeatTempFilename, "firstOverlap.fasta")
dataList = alignerRobot.extractMumData(folderName, "myFirstOverlap"+"Out")
dataList.sort(key = itemgetter(0))
maxVal = -1
maxItm = []
for eachi in dataList:
if eachi[5] > maxVal:
maxVal = eachi[5]
maxItm = eachi
print maxItm
if len(maxItm) > 0 :
repeatStart = maxItm[0]
contigEnd = maxItm[2]
else:
repeatStart = 0
contigEnd = -1
# b) format return : prepare the repeat template
print "ct*lrepeat", int(repeatStart + ct*lrepeat)
print "repeatStart", repeatStart
happyTandemList[contigName]= repeatContentLarge[repeatStart:int(repeatStart + ct*lrepeat)]
contigsTmp[contigName] = tmpCombine[0:contigEnd]
print "len(contigsTmp[contigName])", len(contigsTmp[contigName])
print "len(happyTandemList[contigName])", len(happyTandemList[contigName])
# 7) Combine all the repeat information and do the join
leaderList = [i for i in range(len(contigsTmp))]
for eachrepProfile in loadData:
startContig = eachrepProfile[-1][0][0]
endContig = eachrepProfile[-1][-1][-1]
leaderContig = leaderList[startContig]
leaderName = parseIDToName(leaderContig)
endName = parseIDToName(endContig)
startName = parseIDToName(startContig)
contigsTmp[leaderName] = contigsTmp[leaderName] + happyTandemList[startName]
if endContig != leaderContig:
contigsTmp[leaderName] = contigsTmp[leaderName] + contigsTmp[endName]
contigsTmp[endName] = ""
leaderList[endContig] = leaderContig
leaderAgg = [[] for i in range(len(leaderList))]
for i in range(len(leaderList)):
leaderAgg[leaderList[i]].append(i)
checkingList = [False for i in range(N1)]
fout = open(folderName + "tademResolved.fasta", 'w')
counter = 0
for eachcontig in contigsTmp:
id = abunHouseKeeper.parseEdgeNameToID(eachcontig, 'C')
if checkingList[id/2] == False:
fout.write(">Segkk"+str(counter)+ "\n")
fout.write(contigsTmp[eachcontig])
counter = counter + 1
for eachkk in leaderAgg[leaderList[id]]:
checkingList[eachkk/2] = True
fout.close()
def evaluateCoverage(dataList, lenDic, readLenDic, folderName,mummerLink, continueFilter):
myCountDic = {}
for eachitem in lenDic:
myCountDic[eachitem] = 0
dataList.sort(key = itemgetter(-1))
ctkk, ctbase = 0, 0
toAddBackDic = copy.deepcopy(readLenDic)
for key, items in groupby(dataList, itemgetter(-1)):
maxMatch = -1
bestname = ""
for eachitem in items:
ct = eachitem[6]/100.0 * eachitem[4]
if ct > maxMatch:
maxMatch = ct
bestname = eachitem[-2]
myCountDic[bestname] += readLenDic[key]
ctkk = ctkk + 1
ctbase = ctbase + readLenDic[key]
toAddBackDic[key] = -1
cttot = 0
for eachitem in readLenDic:
cttot = cttot + readLenDic[eachitem]
print "Missed coverage ", (cttot - ctbase)/(4.7*pow(10, 6))
print "percentage miss read", (len(readLenDic) - ctkk)/(1.0*len(readLenDic))
toAddReadList = []
for eachitem in toAddBackDic:
if toAddBackDic[eachitem] >= 0 :
toAddReadList.append(eachitem)
'''
This part need the most parallelism because it is most intense with -l 10
split V, workerList V , combine
'''
if continueFilter:
numberOfFiles= 20
IORobot.putListToFileO(folderName, "raw_reads.fasta" , "selected_raw", toAddReadList)
bindir = os.path.abspath(os.path.dirname(sys.argv[0]))
command = bindir + "/finisherSCCoreLib/fasta-splitter.pl --n-parts " + str(numberOfFiles) + " " + folderName + "selected_raw.fasta"
os.system(command)
workerList = []
for dummyI in range(1, numberOfFiles + 1):
indexOfMum = ""
if dummyI < 10:
indexOfMum = "0" + str(dummyI)
else:
indexOfMum = str(dummyI)
outputName, referenceName, queryName, specialName= "outAbunRefine"+indexOfMum, "improved3.fasta", "selected_raw.part-"+ indexOfMum + ".fasta", "abunMissOut" + indexOfMum
workerList.append([outputName, referenceName, queryName, specialName])
alignerRobot.useMummerAlignBatch(mummerLink, folderName, workerList, houseKeeper.globalParallel ,specialForRaw = True, refinedVersion = True)
alignerRobot.combineMultipleCoorMum( True, mummerLink, folderName, "outAbunRefine", "abunMissOut", numberOfFiles)
for i in range(len(myCountDic)):
eachitem = "Segkk"+str(i)
print eachitem , myCountDic[eachitem]/(1.0*lenDic[eachitem])
myCountDic[eachitem] = myCountDic[eachitem]/(1.0*lenDic[eachitem])
return myCountDic
def evaluateCoverage(dataList, lenDic, readLenDic, folderName, mummerLink,
continueFilter, contigFilename):
'''
not sure if that is the right documentation...
Input : string_graph_3, improved3.fasta, raw_reads.fasta
Output : string_graph_4 with weights [need a data structure to store the weight on node]
Algorithm :
1. Find your favorite mappers to map read back
a. MUMmer, Bowtie, bbmap, any that works V
b. And then write a short parser to parse the results V
2. Calculate count on the abundances
a. Aggregate by taking average [put weights on bin along contigs]
b. Inheritance and a subclass
3. Find your favorite graphical tool to display
a. Use a javascript library [halfviz should just work ! put weight on edge ]
'''
myCountDic = {}
for eachitem in lenDic:
myCountDic[eachitem] = 0
dataList.sort(key=itemgetter(-1))
ctkk, ctbase = 0, 0
toAddBackDic = copy.deepcopy(readLenDic)
for key, items in groupby(dataList, itemgetter(-1)):
maxMatch = -1
bestname = ""
for eachitem in items:
ct = eachitem[6] / 100.0 * eachitem[4]
if ct > maxMatch:
maxMatch = ct
bestname = eachitem[-2]
myCountDic[bestname] += readLenDic[key]
ctkk = ctkk + 1
ctbase = ctbase + readLenDic[key]
toAddBackDic[key] = -1
cttot = 0
for eachitem in readLenDic:
cttot = cttot + readLenDic[eachitem]
print "Missed coverage ", (cttot - ctbase) / (4.7 * pow(10, 6))
print "percentage miss read", (len(readLenDic) - ctkk) / (1.0 *
len(readLenDic))
toAddReadList = []
for eachitem in toAddBackDic:
if toAddBackDic[eachitem] >= 0:
toAddReadList.append(eachitem)
'''
This part need the most parallelism because it is most intense with -l 10
split V, workerList V , combine
'''
if continueFilter:
numberOfFiles = houseKeeper.globalParallelFileNum
IORobot.putListToFileO(folderName, "raw_reads.fasta", "selected_raw",
toAddReadList)
bindir = os.path.abspath(os.path.dirname(sys.argv[0]))
command = bindir + "/finisherSCCoreLib/fasta-splitter.pl --n-parts " + str(
numberOfFiles) + " " + folderName + "selected_raw.fasta"
os.system(command)
workerList = []
for dummyI in range(1, numberOfFiles + 1):
indexOfMum = ""
if dummyI < 10:
indexOfMum = "0" + str(dummyI)
else:
indexOfMum = str(dummyI)
outputName, referenceName, queryName, specialName = "outAbunRefine" + indexOfMum, contigFilename + ".fasta", "selected_raw.part-" + indexOfMum + ".fasta", "abunMissOut" + indexOfMum
workerList.append(
[outputName, referenceName, queryName, specialName])
alignerRobot.useMummerAlignBatch(mummerLink,
folderName,
workerList,
houseKeeper.globalParallel,
specialForRaw=True,
refinedVersion=True)
alignerRobot.combineMultipleCoorMum(True, mummerLink, folderName,
"outAbunRefine", "abunMissOut",
numberOfFiles)
for eachitem in lenDic:
#eachitem = "Segkk"+str(i)
print eachitem, myCountDic[eachitem] / (1.0 * lenDic[eachitem])
myCountDic[eachitem] = myCountDic[eachitem] / (1.0 * lenDic[eachitem])
return myCountDic
