print "\tPool closed"
# Make dictionary to map doubles the ones analyzed:
doubleToAnalyzedDict = {}
for k, l in copyLaterDict.items():
doubleToAnalyzedDict.update(dict([[v, k] for v in l]))
if not options.nocopycache and len(doubleToAnalyzedDict):
# Copy cache files for sequences that occoured more than once:
print "Copying cached results for %d doubles" % len(
doubleToAnalyzedDict)
copyCacheForSequenceDoubles(copyLaterDict, options)
# Calculate the pairwise differences between sequences in each file:
if options.diffs:
pairwisediffs = PairWiseDiffs(options)
pairwisediffs.runPairWiseDiffs(args)
#runPairWiseDiffs(args)
# Summary tree stats:
print 'Computing tree statistics summary...'
treeStatistics = TreeStatistics(options)
treeStatistics.runTreeStatistics(
args,
generateSummary=True,
doubleToAnalyzedDict=doubleToAnalyzedDict,
inputQueryNames=inputQueryNames)
print "done"
# Make HTML output:
print '\tGenerating HTML output...'
def _resultProducer(self, jobID, abortEvent, inputFiles):
try:
sys.stdout = OutputEnqueue()
global optionParser
# Make directories and write fixed inputfiles:
init = Initialize(optionParser.options)
init.createDirs()
inputFiles, seqCount, sequenceNameMap = init.fixAndMoveInput(
inputFiles)
init.checkCacheConsistency(inputFiles)
fastaFileBaseNames = []
try:
alignmentPlugin = findPlugin(optionParser.options.alignment,
'SAP.alignment')
except PluginNotFoundError:
exec("from SAP.Alignment import %s as alignmentPlugin" %
optionParser.options.alignment)
aligner = alignmentPlugin.Aligner(optionParser.options)
try:
assignmentPlugin = findPlugin(optionParser.options.assignment,
'SAP.assignment')
except PluginNotFoundError:
exec("from SAP.Assignment import %s as assignmentPlugin" %
optionParser.options.assignment)
assignment = assignmentPlugin.Assignment(optionParser.options)
uniqueDict = {}
copyLaterDict = {}
homolcompiler = HomolCompiler(optionParser.options)
inputQueryNames = {}
# For each fasta file execute pipeline
for fastaFileName in inputFiles:
fastaFile = open(fastaFileName, 'r')
fastaIterator = Fasta.Iterator(fastaFile,
parser=Fasta.RecordParser())
fastaFileBaseName = os.path.splitext(
os.path.basename(fastaFileName))[0]
fastaFileBaseNames.append(fastaFileBaseName)
if abortEvent():
return jobID
inputQueryNames[fastaFileBaseName] = {}
for fastaRecord in fastaIterator:
# Discard the header except for the first id word:
fastaRecord.title = re.search(r'^(\S+)',
fastaRecord.title).group(1)
inputQueryNames[fastaFileBaseName][
fastaRecord.title] = True
print "%s -> %s: " % (fastaFileBaseName, fastaRecord.title)
# See if the sequence is been encountered before and if so skip it for now:
if uniqueDict.has_key(fastaRecord.sequence):
copyLaterDict.setdefault(
uniqueDict[fastaRecord.sequence],
[]).append('%s_%s' %
(fastaFileBaseName, fastaRecord.title))
print '\tsequence double - skipping...\n'
continue
else:
uniqueDict[fastaRecord.sequence] = '%s_%s' % (
fastaFileBaseName, fastaRecord.title)
# Find homologues: Fasta files and pickled homologyResult objects are written to homologcache
homologyResult = homolcompiler.compileHomologueSet(
fastaRecord, fastaFileBaseName)
if abortEvent():
return jobID
if homologyResult != None:
# The homologyResult object serves as a job carrying the relevant information.
aligner.align(
os.path.join(optionParser.options.homologcache,
homologyResult.homologuesFileName))
if abortEvent():
return jobID
try:
assignment.run(
os.path.join(
optionParser.options.alignmentcache,
homologyResult.alignmentFileName))
except assignmentPlugin.AssignmentError, X:
print X.msg
if abortEvent():
return jobID
treeStatistics = TreeStatistics(optionParser.options)
treeStatistics.runTreeStatistics([
os.path.join(
optionParser.options.homologcache,
homologyResult.homologuesPickleFileName)
],
generateSummary=False)
if abortEvent():
return jobID
fastaFile.close()
if abortEvent():
return jobID
# # Calculate the pairwise differences between sequences in each file:
# if optionParser.options.diffs:
# pairwisediffs = PairWiseDiffs(optionParser.options)
# pairwisediffs.runPairWiseDiffs(inputFiles)
# #runPairWiseDiffs(inputFiles)
#
# if abortEvent():
# return jobID
# Make dictionary to map doubles the ones analyzed:
doubleToAnalyzedDict = {}
for k, l in copyLaterDict.items():
doubleToAnalyzedDict.update(dict([[v, k] for v in l]))
if not optionParser.options.nocopycache and len(
doubleToAnalyzedDict):
# Copy cache files for sequences that occoured more than once:
print "Copying cached results for %d doubles" % len(
doubleToAnalyzedDict)
copyCacheForSequenceDoubles(copyLaterDict,
optionParser.options)
# Calculate the pairwise differences between sequences in each file:
if optionParser.options.diffs:
pairwisediffs = PairWiseDiffs(optionParser.options)
pairwisediffs.runPairWiseDiffs(inputFiles)
if abortEvent():
return jobID
# Summary tree stats:
print 'Computing tree statistics summary...'
treeStatistics = TreeStatistics(optionParser.options)
treeStatistics.runTreeStatistics(
inputFiles,
generateSummary=True,
doubleToAnalyzedDict=doubleToAnalyzedDict,
inputQueryNames=inputQueryNames)
print "done"
if abortEvent():
return jobID
# Make HTML output:
print '\tGenerating HTML output...'
resultHTML = ResultHTML(optionParser.options)
resultHTML.webify(
[optionParser.options.treestatscache + '/summary.pickle'],
fastaFileBaseNames, doubleToAnalyzedDict, sequenceNameMap)
print 'done'
return jobID
def _resultProducer(self, jobID, abortEvent, inputFiles):
try:
sys.stdout = OutputEnqueue()
global optionParser
# Make directories and write fixed inputfiles:
init = Initialize(optionParser.options)
init.createDirs()
inputFiles, seqCount, sequenceNameMap = init.fixAndMoveInput(inputFiles)
init.checkCacheConsistency(inputFiles)
fastaFileBaseNames = []
try:
alignmentPlugin = findPlugin(optionParser.options.alignment, 'SAP.alignment')
except PluginNotFoundError:
exec("from SAP.Alignment import %s as alignmentPlugin" % optionParser.options.alignment)
aligner = alignmentPlugin.Aligner(optionParser.options)
try:
assignmentPlugin = findPlugin(optionParser.options.assignment, 'SAP.assignment')
except PluginNotFoundError:
exec("from SAP.Assignment import %s as assignmentPlugin" % optionParser.options.assignment)
assignment = assignmentPlugin.Assignment(optionParser.options)
uniqueDict = {}
copyLaterDict = {}
homolcompiler = HomolCompiler(optionParser.options)
inputQueryNames = {}
# For each fasta file execute pipeline
for fastaFileName in inputFiles:
fastaFile = open(fastaFileName, 'r')
fastaIterator = Fasta.Iterator(fastaFile, parser=Fasta.RecordParser())
fastaFileBaseName = os.path.splitext(os.path.basename(fastaFileName))[0]
fastaFileBaseNames.append(fastaFileBaseName)
if abortEvent():
return jobID
inputQueryNames[fastaFileBaseName] = {}
for fastaRecord in fastaIterator:
# Discard the header except for the first id word:
fastaRecord.title = re.search(r'^(\S+)', fastaRecord.title).group(1)
inputQueryNames[fastaFileBaseName][fastaRecord.title] = True
print "%s -> %s: " % (fastaFileBaseName, fastaRecord.title)
# See if the sequence is been encountered before and if so skip it for now:
if uniqueDict.has_key(fastaRecord.sequence):
copyLaterDict.setdefault(uniqueDict[fastaRecord.sequence], []).append('%s_%s' % (fastaFileBaseName, fastaRecord.title))
print '\tsequence double - skipping...\n'
continue
else:
uniqueDict[fastaRecord.sequence] = '%s_%s' % (fastaFileBaseName, fastaRecord.title)
# Find homologues: Fasta files and pickled homologyResult objects are written to homologcache
homologyResult = homolcompiler.compileHomologueSet(fastaRecord, fastaFileBaseName)
if abortEvent():
return jobID
if homologyResult != None:
# The homologyResult object serves as a job carrying the relevant information.
aligner.align(os.path.join(optionParser.options.homologcache, homologyResult.homologuesFileName))
if abortEvent():
return jobID
try:
assignment.run(os.path.join(optionParser.options.alignmentcache, homologyResult.alignmentFileName))
except assignmentPlugin.AssignmentError, X:
print X.msg
if abortEvent():
return jobID
treeStatistics = TreeStatistics(optionParser.options)
treeStatistics.runTreeStatistics([os.path.join(optionParser.options.homologcache, homologyResult.homologuesPickleFileName)], generateSummary=False)
if abortEvent():
return jobID
fastaFile.close()
if abortEvent():
return jobID
# # Calculate the pairwise differences between sequences in each file:
# if optionParser.options.diffs:
# pairwisediffs = PairWiseDiffs(optionParser.options)
# pairwisediffs.runPairWiseDiffs(inputFiles)
# #runPairWiseDiffs(inputFiles)
#
# if abortEvent():
# return jobID
# Make dictionary to map doubles the ones analyzed:
doubleToAnalyzedDict = {}
for k, l in copyLaterDict.items():
doubleToAnalyzedDict.update(dict([[v,k] for v in l]))
if not optionParser.options.nocopycache and len(doubleToAnalyzedDict):
# Copy cache files for sequences that occoured more than once:
print "Copying cached results for %d doubles" % len(doubleToAnalyzedDict)
copyCacheForSequenceDoubles(copyLaterDict, optionParser.options)
# Calculate the pairwise differences between sequences in each file:
if optionParser.options.diffs:
pairwisediffs = PairWiseDiffs(optionParser.options)
pairwisediffs.runPairWiseDiffs(inputFiles)
if abortEvent():
return jobID
# Summary tree stats:
print 'Computing tree statistics summary...'
treeStatistics = TreeStatistics(optionParser.options)
treeStatistics.runTreeStatistics(inputFiles, generateSummary=True, doubleToAnalyzedDict=doubleToAnalyzedDict, inputQueryNames=inputQueryNames)
print "done"
if abortEvent():
return jobID
# Make HTML output:
print '\tGenerating HTML output...'
resultHTML = ResultHTML(optionParser.options)
resultHTML.webify([optionParser.options.treestatscache + '/summary.pickle'], fastaFileBaseNames, doubleToAnalyzedDict, sequenceNameMap)
print 'done'
return jobID
poolStatus(pool)
print "\tPool closed"
# Make dictionary to map doubles the ones analyzed:
doubleToAnalyzedDict = {}
for k, l in copyLaterDict.items():
doubleToAnalyzedDict.update(dict([[v,k] for v in l]))
if not options.nocopycache and len(doubleToAnalyzedDict):
# Copy cache files for sequences that occoured more than once:
print "Copying cached results for %d doubles" % len(doubleToAnalyzedDict)
copyCacheForSequenceDoubles(copyLaterDict, options)
# Calculate the pairwise differences between sequences in each file:
if options.diffs:
pairwisediffs = PairWiseDiffs(options)
pairwisediffs.runPairWiseDiffs(args)
#runPairWiseDiffs(args)
# Summary tree stats:
print 'Computing tree statistics summary...'
treeStatistics = TreeStatistics(options)
treeStatistics.runTreeStatistics(args, generateSummary=True, doubleToAnalyzedDict=doubleToAnalyzedDict, inputQueryNames=inputQueryNames)
print "done"
# Make HTML output:
print '\tGenerating HTML output...'
resultHTML = ResultHTML(options)
resultHTML.webify([options.treestatscache + '/summary.pickle'], fastaFileBaseNames, doubleToAnalyzedDict, sequenceNameMap)
print 'done'
def run_analysis(self, input_file, options, stdout_file, stderr_file, email):
class RedirectStdStreams(object):
def __init__(self, stdout=None, stderr=None):
if stdout is not None:
stdout = open(stdout, 'w')
if stderr is not None:
stderr = open(stderr, 'w')
self.stdout = stdout
self.stderr = stderr
self._stdout = stdout or sys.stdout
self._stderr = stderr or sys.stderr
def __enter__(self):
self.old_stdout, self.old_stderr = sys.stdout, sys.stderr
self.old_stdout.flush()
self.old_stderr.flush()
sys.stdout, sys.stderr = self._stdout, self._stderr
def __exit__(self, exc_type, exc_value, traceback):
self._stdout.flush()
self._stderr.flush()
if sys.stdout is self.stdout:
sys.stdout.close()
if sys.stderr is self.stderr:
sys.stderr.close()
sys.stdout = self.old_stdout
sys.stderr = self.old_stderr
with RedirectStdStreams(stdout=stdout_file, stderr=stderr_file):
# Make directories and write fixed inputfiles:
init = Initialize(options)
init.createDirs()
inputFiles, seqCount, sequenceNameMap = init.fixAndMoveInput(
[input_file])
init.checkCacheConsistency(inputFiles)
progress = 1
self.update_state(state='PROGRESS',
meta={
'current': progress,
'total': seqCount * 4 + 2
})
fastaFileBaseNames = []
try:
alignmentPlugin = findPlugin(options.alignment, 'SAP.alignment')
except PluginNotFoundError:
from SAP.Alignment import Clustalw2 as alignmentPlugin
# exec("from SAP.Alignment import %s as alignmentPlugin" % options.alignment)
aligner = alignmentPlugin.Aligner(options)
try:
assignmentPlugin = findPlugin(options.assignment, 'SAP.assignment')
except PluginNotFoundError:
if options.assignment == "Barcoder":
from SAP.Assignment import Barcoder as assignmentPlugin
elif options.assignment == "ConstrainedNJ":
from SAP.Assignment import ConstrainedNJ as assignmentPlugin
else:
assert 0
# exec("from SAP.Assignment import %s as assignmentPlugin" % options.assignment)
assignment = assignmentPlugin.Assignment(options)
uniqueDict = {}
copyLaterDict = {}
homolcompiler = HomolCompiler(options)
inputQueryNames = {}
# For each fasta file execute pipeline
for fastaFileName in inputFiles:
fastaFile = open(fastaFileName, 'r')
fastaIterator = Fasta.Iterator(fastaFile,
parser=Fasta.RecordParser())
fastaFileBaseName = os.path.splitext(
os.path.basename(fastaFileName))[0]
fastaFileBaseNames.append(fastaFileBaseName)
inputQueryNames[fastaFileBaseName] = {}
for fastaRecord in fastaIterator:
# Discard the header except for the first id word:
fastaRecord.title = re.search(r'^(\S+)',
fastaRecord.title).group(1)
app.logger.info("file: {}, query: {}".format(
fastaFileBaseName, fastaRecord.title))
inputQueryNames[fastaFileBaseName][fastaRecord.title] = True
print "%s -> %s: " % (fastaFileBaseName, fastaRecord.title)
# See if the sequence is been encountered before and if so skip it for now:
if uniqueDict.has_key(fastaRecord.sequence):
copyLaterDict.setdefault(
uniqueDict[fastaRecord.sequence], []).append(
'%s_%s' % (fastaFileBaseName, fastaRecord.title))
print '\tsequence double - skipping...\n'
continue
else:
uniqueDict[fastaRecord.sequence] = '%s_%s' % (
fastaFileBaseName, fastaRecord.title)
# Find homologues: Fasta files and pickled homologyResult objects are written to homologcache
homologyResult = homolcompiler.compileHomologueSet(
fastaRecord, fastaFileBaseName)
progress += 1
self.update_state(state='PROGRESS',
meta={
'current': progress,
'total': seqCount * 4 + 2
})
if homologyResult is not None:
# The homologyResult object serves as a job carrying the relevant information.
aligner.align(
os.path.join(options.homologcache,
homologyResult.homologuesFileName))
progress += 1
self.update_state(state='PROGRESS',
meta={
'current': progress,
'total': seqCount * 4 + 2
})
try:
assignment.run(
os.path.join(options.alignmentcache,
homologyResult.alignmentFileName))
except assignmentPlugin.AssignmentError, X:
print X.msg
progress += 1
self.update_state(state='PROGRESS',
meta={
'current': progress,
'total': seqCount * 4 + 2
})
treeStatistics = TreeStatistics(options)
treeStatistics.runTreeStatistics([
os.path.join(options.homologcache,
homologyResult.homologuesPickleFileName)
],
generateSummary=False)
progress += 1
self.update_state(state='PROGRESS',
meta={
'current': progress,
'total': seqCount * 4 + 2
})
else:
progress += 3
self.update_state(state='PROGRESS',
meta={
'current': progress,
'total': seqCount * 4 + 2
})
fastaFile.close()
# Make dictionary to map doubles the ones analyzed:
doubleToAnalyzedDict = {}
for k, l in copyLaterDict.items():
doubleToAnalyzedDict.update(dict([[v, k] for v in l]))
if not options.nocopycache and len(doubleToAnalyzedDict):
# Copy cache files for sequences that occoured more than once:
print "Copying cached results for %d doubles" % len(
doubleToAnalyzedDict)
copyCacheForSequenceDoubles(copyLaterDict, options)
# Calculate the pairwise differences between sequences in each file:
if options.diffs:
pairwisediffs = PairWiseDiffs(options)
pairwisediffs.runPairWiseDiffs(inputFiles)
# Summary tree stats:
print 'Computing tree statistics summary...'
treeStatistics = TreeStatistics(options)
treeStatistics.runTreeStatistics(
inputFiles,
generateSummary=True,
doubleToAnalyzedDict=doubleToAnalyzedDict,
inputQueryNames=inputQueryNames)
print "done"
progress += 1
self.update_state(state='PROGRESS',
meta={
'current': progress,
'total': seqCount * 4 + 2
})
# Make HTML output:
print '\tGenerating HTML output...'
resultHTML = ResultHTML(options)
resultHTML.webify([options.treestatscache + '/summary.pickle'],
fastaFileBaseNames, doubleToAnalyzedDict,
sequenceNameMap)
print 'done'
# clean up files we won't need anyway
shutil.rmtree(options.datadir)
shutil.rmtree(options.homologcache)
shutil.rmtree(options.blastcache)
shutil.rmtree(options.dbcache)
shutil.rmtree(options.treescache)
shutil.rmtree(options.alignmentcache)
def run_analysis(self, input_file, options, stdout_file, stderr_file, email):
class RedirectStdStreams(object):
def __init__(self, stdout=None, stderr=None):
if stdout is not None:
stdout = open(stdout, 'w')
if stderr is not None:
stderr = open(stderr, 'w')
self.stdout = stdout
self.stderr = stderr
self._stdout = stdout or sys.stdout
self._stderr = stderr or sys.stderr
def __enter__(self):
self.old_stdout, self.old_stderr = sys.stdout, sys.stderr
self.old_stdout.flush()
self.old_stderr.flush()
sys.stdout, sys.stderr = self._stdout, self._stderr
def __exit__(self, exc_type, exc_value, traceback):
self._stdout.flush(); self._stderr.flush()
if sys.stdout is self.stdout:
sys.stdout.close()
if sys.stderr is self.stderr:
sys.stderr.close()
sys.stdout = self.old_stdout
sys.stderr = self.old_stderr
with RedirectStdStreams(stdout=stdout_file, stderr=stderr_file):
# Make directories and write fixed inputfiles:
init = Initialize(options)
init.createDirs()
inputFiles, seqCount, sequenceNameMap = init.fixAndMoveInput([input_file])
init.checkCacheConsistency(inputFiles)
progress = 1
self.update_state(state='PROGRESS', meta={'current': progress, 'total': seqCount*4+2})
fastaFileBaseNames = []
try:
alignmentPlugin = findPlugin(options.alignment, 'SAP.alignment')
except PluginNotFoundError:
from SAP.Alignment import Clustalw2 as alignmentPlugin
# exec("from SAP.Alignment import %s as alignmentPlugin" % options.alignment)
aligner = alignmentPlugin.Aligner(options)
try:
assignmentPlugin = findPlugin(options.assignment, 'SAP.assignment')
except PluginNotFoundError:
if options.assignment == "Barcoder":
from SAP.Assignment import Barcoder as assignmentPlugin
elif options.assignment == "ConstrainedNJ":
from SAP.Assignment import ConstrainedNJ as assignmentPlugin
else:
assert 0
# exec("from SAP.Assignment import %s as assignmentPlugin" % options.assignment)
assignment = assignmentPlugin.Assignment(options)
uniqueDict = {}
copyLaterDict = {}
homolcompiler = HomolCompiler(options)
inputQueryNames = {}
# For each fasta file execute pipeline
for fastaFileName in inputFiles:
fastaFile = open(fastaFileName, 'r')
fastaIterator = Fasta.Iterator(fastaFile, parser=Fasta.RecordParser())
fastaFileBaseName = os.path.splitext(os.path.basename(fastaFileName))[0]
fastaFileBaseNames.append(fastaFileBaseName)
inputQueryNames[fastaFileBaseName] = {}
for fastaRecord in fastaIterator:
# Discard the header except for the first id word:
fastaRecord.title = re.search(r'^(\S+)', fastaRecord.title).group(1)
app.logger.info("file: {}, query: {}".format(fastaFileBaseName, fastaRecord.title))
inputQueryNames[fastaFileBaseName][fastaRecord.title] = True
print "%s -> %s: " % (fastaFileBaseName, fastaRecord.title)
# See if the sequence is been encountered before and if so skip it for now:
if uniqueDict.has_key(fastaRecord.sequence):
copyLaterDict.setdefault(uniqueDict[fastaRecord.sequence], []).append('%s_%s' % (fastaFileBaseName, fastaRecord.title))
print '\tsequence double - skipping...\n'
continue
else:
uniqueDict[fastaRecord.sequence] = '%s_%s' % (fastaFileBaseName, fastaRecord.title)
# Find homologues: Fasta files and pickled homologyResult objects are written to homologcache
homologyResult = homolcompiler.compileHomologueSet(fastaRecord, fastaFileBaseName)
progress += 1
self.update_state(state='PROGRESS', meta={'current': progress, 'total': seqCount*4+2})
if homologyResult is not None:
# The homologyResult object serves as a job carrying the relevant information.
aligner.align(os.path.join(options.homologcache, homologyResult.homologuesFileName))
progress += 1
self.update_state(state='PROGRESS', meta={'current': progress, 'total': seqCount*4+2})
try:
assignment.run(os.path.join(options.alignmentcache, homologyResult.alignmentFileName))
except assignmentPlugin.AssignmentError, X:
print X.msg
progress += 1
self.update_state(state='PROGRESS', meta={'current': progress, 'total': seqCount*4+2})
treeStatistics = TreeStatistics(options)
treeStatistics.runTreeStatistics([os.path.join(options.homologcache, homologyResult.homologuesPickleFileName)], generateSummary=False)
progress += 1
self.update_state(state='PROGRESS', meta={'current': progress, 'total': seqCount*4+2})
else:
progress += 3
self.update_state(state='PROGRESS', meta={'current': progress, 'total': seqCount*4+2})
fastaFile.close()
# Make dictionary to map doubles the ones analyzed:
doubleToAnalyzedDict = {}
for k, l in copyLaterDict.items():
doubleToAnalyzedDict.update(dict([[v,k] for v in l]))
if not options.nocopycache and len(doubleToAnalyzedDict):
# Copy cache files for sequences that occoured more than once:
print "Copying cached results for %d doubles" % len(doubleToAnalyzedDict)
copyCacheForSequenceDoubles(copyLaterDict, options)
# Calculate the pairwise differences between sequences in each file:
if options.diffs:
pairwisediffs = PairWiseDiffs(options)
pairwisediffs.runPairWiseDiffs(inputFiles)
# Summary tree stats:
print 'Computing tree statistics summary...'
treeStatistics = TreeStatistics(options)
treeStatistics.runTreeStatistics(inputFiles, generateSummary=True, doubleToAnalyzedDict=doubleToAnalyzedDict, inputQueryNames=inputQueryNames)
print "done"
progress += 1
self.update_state(state='PROGRESS', meta={'current': progress, 'total': seqCount*4+2})
# Make HTML output:
print '\tGenerating HTML output...'
resultHTML = ResultHTML(options)
resultHTML.webify([options.treestatscache + '/summary.pickle'], fastaFileBaseNames, doubleToAnalyzedDict, sequenceNameMap)
print 'done'
# clean up files we won't need anyway
shutil.rmtree(options.datadir)
shutil.rmtree(options.homologcache)
shutil.rmtree(options.blastcache)
shutil.rmtree(options.dbcache)
shutil.rmtree(options.treescache)
shutil.rmtree(options.alignmentcache)
