def alignerSubRoutine(folderName, referenceFile, queryFile, mummerLink,
header):
#alignerRobot.useMummerAlign(mummerLink, folderName, header, referenceFile, queryFile)
numberOfFiles = houseKeeper.globalParallelFileNum
bindir = os.path.abspath(os.path.dirname(sys.argv[0]))
command = bindir + "/finisherSCCoreLib/fasta-splitter.pl --n-parts " + str(
numberOfFiles) + " " + folderName + queryFile
os.system(command)
os.system("cp *.fasta " + folderName)
os.system("rm *.fasta ")
workerList = []
for dummyI in range(1, numberOfFiles + 1):
indexOfMum = ""
if dummyI < 10:
indexOfMum = "0" + str(dummyI)
else:
indexOfMum = str(dummyI)
outputName, referenceName, queryName, specialName = header + indexOfMum, referenceFile, queryFile[
0:-6] + ".part-" + indexOfMum + ".fasta", header + indexOfMum
workerList.append([outputName, referenceName, queryName, specialName])
alignerRobot.useMummerAlignBatch(mummerLink,
folderName,
workerList,
houseKeeper.globalParallel,
specialForRaw=False,
refinedVersion=False)
alignerRobot.combineMultipleCoorMum(True, mummerLink, folderName, header,
header + "Out", numberOfFiles)
def alignerSubRoutine(folderName ,referenceFile, queryFile, mummerLink, header ):
#alignerRobot.useMummerAlign(mummerLink, folderName, header, referenceFile, queryFile)
numberOfFiles = 20
bindir = os.path.abspath(os.path.dirname(sys.argv[0]))
command = bindir + "/finisherSCCoreLib/fasta-splitter.pl --n-parts " + str(numberOfFiles) + " " + folderName + queryFile
os.system(command)
os.system("cp *.fasta " + folderName )
os.system("rm *.fasta ")
workerList = []
for dummyI in range(1, numberOfFiles + 1):
indexOfMum = ""
if dummyI < 10:
indexOfMum = "0" + str(dummyI)
else:
indexOfMum = str(dummyI)
outputName, referenceName, queryName, specialName= header+indexOfMum, referenceFile,queryFile[0:-6]+".part-"+ indexOfMum + ".fasta" , header + indexOfMum
workerList.append([outputName, referenceName, queryName, specialName])
alignerRobot.useMummerAlignBatch(mummerLink, folderName, workerList, houseKeeper.globalParallel ,specialForRaw = False, refinedVersion = False)
alignerRobot.combineMultipleCoorMum( True, mummerLink, folderName, header,header +"Out", numberOfFiles)
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):
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
