def parseCustomBed(bedInputFilePaths,
genomeFilePath,
stratifyByMS,
stratifyByMutSig,
separateIndividualCohorts,
onlySingleBaseSubs=False,
includeIndels=False):
if onlySingleBaseSubs and includeIndels:
raise UserInputError(
"Indels are incompatible with single nucleotide substitutions.")
if len(bedInputFilePaths) == 0:
raise UserInputError("No bed files were found to parse.")
for bedInputFilePath in bedInputFilePaths:
print("\nWorking in:", os.path.basename(bedInputFilePath))
# Get some important file system paths for the rest of the function and generate metadata
# If this is an intermediate file, keep in mind that it's not in the data group's root directory
# and metadata should already have been generated elsewhere
if getIsolatedParentDir(bedInputFilePath) == "intermediate_files":
dataDirectory = os.path.dirname(os.path.dirname(bedInputFilePath))
else:
dataDirectory = os.path.dirname(bedInputFilePath)
generateMetadata(os.path.basename(dataDirectory),
getIsolatedParentDir(genomeFilePath),
os.path.basename(bedInputFilePath),
InputFormat.customBed,
os.path.dirname(bedInputFilePath))
intermediateFilesDir = os.path.join(dataDirectory,
"intermediate_files")
checkDirs(intermediateFilesDir)
autoAcquiredFilePath = os.path.join(intermediateFilesDir,
"auto_acquire.fa")
context = autoAcquireAndQACheck(bedInputFilePath, genomeFilePath,
autoAcquiredFilePath,
onlySingleBaseSubs, includeIndels)
# Make sure the input file is not named the same as what will become the output file. If it is, it needs to be copied
# to the intermediate_files directory so it is available to be read from as the new output file is being written.
expectedOutputFilePath = generateFilePath(
directory=dataDirectory,
dataGroup=os.path.basename(dataDirectory),
context=context,
dataType=DataTypeStr.mutations,
fileExtension=".bed")
if bedInputFilePath == expectedOutputFilePath:
inputFilePathCopy = os.path.join(
intermediateFilesDir, os.path.basename(bedInputFilePath))
print(
"Input file path is identical to generated output file path and will be overwritten. ",
"Creating a copy of the input file at:", inputFilePathCopy,
"to use for reading.")
shutil.copy2(bedInputFilePath, inputFilePathCopy)
bedInputFilePath = inputFilePathCopy
# Create an instance of the WriteManager to handle writing.
with WriteManager(dataDirectory, context) as writeManager:
# Check to see if cohort designations are present to see if preparations need to be made.
optionalArgument = tuple()
with open(bedInputFilePath, 'r') as bedInputFile:
line = bedInputFile.readline()
# Is the cohort designation present?
if len(line.strip().split('\t')) == 7:
# Include in sort function
optionalArgument = ("-k7,7", )
# Prepare the write manager for individual cohorts if desired.
if separateIndividualCohorts:
writeManager.setUpForIndividualCohorts()
elif stratifyByMS or stratifyByMutSig:
raise UserInputError(
"Additional stratification given, but no cohort designation given."
)
elif separateIndividualCohorts:
raise UserInputError(
"Separation by individual cohorts requested, but no cohort designation given."
)
# Sort the input data (should also ensure that the output data is sorted)
subprocess.run(("sort", ) + optionalArgument +
("-k1,1", "-k2,2n", "-k3,3n", bedInputFilePath,
"-s", "-o", bedInputFilePath),
check=True)
# If requested, also prepare for stratification by microsatellite stability.
if stratifyByMS:
setUpForMSStratification(writeManager, bedInputFilePath)
if stratifyByMutSig:
setUpForMutSigStratification(writeManager, bedInputFilePath)
# Go, go, go!
convertToStandardInput(bedInputFilePath, writeManager,
onlySingleBaseSubs, includeIndels)
def parseKucabCompendium(kucabSubstitutionsFilePaths: List[str],
genomeFilePath, nucPosFilePath, includeAllPAHs):
for kucabSubstitutionsFilePath in kucabSubstitutionsFilePaths:
print("\nWorking in:", os.path.basename(kucabSubstitutionsFilePath))
if not kucabSubstitutionsFilePath.endswith("final.txt"):
raise InvalidPathError(
kucabSubstitutionsFilePath,
"Given kucab input file does not end in \"final.txt\":")
# Prepare the output file path.
localRootDirectory = os.path.dirname(kucabSubstitutionsFilePath)
dataGroupName = getIsolatedParentDir(kucabSubstitutionsFilePath)
if includeAllPAHs:
outputDirectory = os.path.join(localRootDirectory, "all_PAHs")
dataGroupName += "_all_PAHs"
else:
dataGroupName += "_smoker_lung"
outputDirectory = os.path.join(localRootDirectory, "smoker_lung")
# Make sure the data directory exists.
if not os.path.exists(outputDirectory): os.mkdir(outputDirectory)
# Generate the output file path and metadata
outputTrinucBedFilePath = generateFilePath(
directory=outputDirectory,
dataGroup=dataGroupName,
context="trinuc",
dataType=DataTypeStr.mutations,
fileExtension=".bed")
generateMetadata(
dataGroupName, getIsolatedParentDir(genomeFilePath),
getIsolatedParentDir(nucPosFilePath),
os.path.join("..", os.path.basename(kucabSubstitutionsFilePath)),
outputDirectory)
# Get the list of acceptable chromosomes
acceptableChromosomes = getAcceptableChromosomes(genomeFilePath)
# These are the designations for PAH mutation signatures, the ones related to tobacco smoke that we want to study.
PAHDesignations = ("MSM0.54", "MSM0.26", "MSM0.92", "MSM0.2",
"MSM0.42", "MSM0.74", "MSM0.103"
"MSM0.14", "MSM0.82", "MSM0.130", "MSM0.12",
"MSM0.132", "MSM0.13", "MSM0.96")
# These designations specifically mimic the indel signature in smokers' lung cancer tumors.
LungCancerSpecificDesignations = ("MSM0.26", "MSM0.92", "MSM0.2",
"MSM0.103", "MSM0.14")
# Set the designations that will be used to collect data based on the input to the function.
if includeAllPAHs:
relevantDesignations = PAHDesignations
else:
relevantDesignations = LungCancerSpecificDesignations
print("Reading data and writing to trinuc bed file...")
with open(kucabSubstitutionsFilePath, 'r') as kucabSubstitutionsFile:
with open(outputTrinucBedFilePath, 'w') as outputTrinucBedFile:
firstLineFlag = True
for line in kucabSubstitutionsFile:
# Skip the first line with headers.
if firstLineFlag:
firstLineFlag = False
continue
# The lines are separated by tabs. The relevant data have the following indices in a tab-separated list:
# 15: mutagen designation
# 4: Chromosome
# 5: Start Pos (1 base)
# 6: Reference base
# 7: Mutated base
# 13: pre-base context
# 14: post-base context
choppedUpLine = line.strip().split('\t')
# Skip the mutation if it does not belong to the relevant group.
if not choppedUpLine[15] in relevantDesignations: continue
# Compile the necessary information for the bed file.
chromosome = "chr" + choppedUpLine[4]
# Handle the weird chromsome formatting and then check for invalid chromosomes.
if chromosome == "chr23": chromosome = "chrX"
if chromosome == "chr24": chromosome = "chrY"
if not chromosome in acceptableChromosomes: continue
startPos1Base = choppedUpLine[5]
startPos0Base = str(int(startPos1Base) - 1)
mutatedFrom = choppedUpLine[6]
mutatedTo = choppedUpLine[7]
trinucContext = ''.join(
(choppedUpLine[13], mutatedFrom, choppedUpLine[14]))
# If the mutated base is listed as arising from a purine, flip the mutation and the strand.
if isPurine(mutatedFrom):
mutation = reverseCompliment(
mutatedFrom) + '>' + reverseCompliment(mutatedTo)
strand = '-'
trinucContext = reverseCompliment(trinucContext)
else:
mutation = mutatedFrom + '>' + mutatedTo
strand = '+'
# Write the information to the trinuc bed file.
outputTrinucBedFile.write('\t'.join(
(chromosome, startPos0Base, startPos1Base,
trinucContext, mutation, strand)) + '\n')
# Sort the output file.
print("Sorting output file...")
subprocess.run(("sort", "-k1,1", "-k2,2n", outputTrinucBedFilePath,
"-o", outputTrinucBedFilePath),
check=True)