def add(self, virusTitle, sampleName):
"""
Add a a virus title, sample name combination and get its FASTA file
name. Write the FASTA file if it does not already exist.
@param virusTitle: A C{str} virus title.
@param sampleName: A C{str} sample name.
@return: A C{str} FASTA file name holding all the reads (without
duplicates) from the sample that matched the proteins in the given
virus.
"""
virusIndex = self._viruses.setdefault(virusTitle, len(self._viruses))
sampleIndex = self._samples.setdefault(sampleName, len(self._samples))
try:
return self._fastaFilenames[(virusIndex, sampleIndex)]
except KeyError:
result = Reads()
for proteinMatch in self._proteinGrouper.virusTitles[
virusTitle][sampleName]:
for read in FastaReads(proteinMatch['fastaFilename'],
checkAlphabet=0):
result.add(read)
saveFilename = join(
proteinMatch['outDir'],
'virus-%d-sample-%d.fasta' % (virusIndex, sampleIndex))
result.filter(removeDuplicates=True).save(saveFilename)
self._fastaFilenames[(virusIndex, sampleIndex)] = saveFilename
return saveFilename
def add(self, pathogenName, sampleName):
"""
Add a (pathogen name, sample name) combination and get its FASTA/FASTQ
file name and unique read count. Write the FASTA/FASTQ file if it does
not already exist. Save the unique read count into
C{self._proteinGrouper}.
@param pathogenName: A C{str} pathogen name.
@param sampleName: A C{str} sample name.
@return: A C{str} giving the FASTA/FASTQ file name holding all the
reads (without duplicates, by id) from the sample that matched the
proteins in the given pathogen.
"""
pathogenIndex = self._pathogens.setdefault(pathogenName,
len(self._pathogens))
sampleIndex = self._samples.setdefault(sampleName, len(self._samples))
try:
return self._readsFilenames[(pathogenIndex, sampleIndex)]
except KeyError:
reads = Reads()
for proteinMatch in self._proteinGrouper.pathogenNames[
pathogenName][sampleName]['proteins'].values():
for read in self._readsClass(proteinMatch['readsFilename']):
reads.add(read)
saveFilename = join(
proteinMatch['outDir'], 'pathogen-%d-sample-%d.%s' %
(pathogenIndex, sampleIndex, self._format))
reads.filter(removeDuplicatesById=True)
nReads = reads.save(saveFilename, format_=self._format)
# Save the unique read count into self._proteinGrouper
self._proteinGrouper.pathogenNames[pathogenName][sampleName][
'uniqueReadCount'] = nReads
self._readsFilenames[(pathogenIndex, sampleIndex)] = saveFilename
return saveFilename
def testFilterOnMaxLength(self):
"""
Filtering on maximal length must work.
"""
reads = Reads()
read1 = Read('id1', 'ATCG')
read2 = Read('id2', 'ACG')
reads.add(read1)
reads.add(read2)
result = reads.filter(maxLength=3)
self.assertEqual([read2], list(result))
def testFilterWithMinLengthEqualToMaxLength(self):
"""
When filtering on length, a read should be returned if its length
equals a passed minimum and maximum length.
"""
reads = Reads()
read1 = Read('id1', 'ATCG')
read2 = Read('id2', 'ACG')
reads.add(read1)
reads.add(read2)
result = reads.filter(minLength=4, maxLength=4)
self.assertEqual([read1], list(result))
def testFilterOnLengthEverythingMatches(self):
"""
When filtering on length, all reads should be returned if they all
satisfy the length requirements.
"""
reads = Reads()
read1 = Read('id1', 'ATCG')
read2 = Read('id2', 'ACG')
reads.add(read1)
reads.add(read2)
result = reads.filter(minLength=2, maxLength=5)
self.assertEqual([read1, read2], list(result))
def testFilterOnLengthNothingMatches(self):
"""
When filtering on length, no reads should be returned if none of them
satisfy the length requirements.
"""
reads = Reads()
read1 = Read('id1', 'ATCG')
read2 = Read('id2', 'ACG')
reads.add(read1)
reads.add(read2)
result = reads.filter(minLength=10, maxLength=15)
self.assertEqual([], list(result))
def add(self, pathogenName, sampleName):
"""
Add a (pathogen name, sample name) combination and get its FASTA/FASTQ
file name and unique read count. Write the FASTA/FASTQ file if it does
not already exist. Save the unique read count into
C{self._proteinGrouper}.
@param pathogenName: A C{str} pathogen name.
@param sampleName: A C{str} sample name.
@return: A C{str} giving the FASTA/FASTQ file name holding all the
reads (without duplicates, by id) from the sample that matched the
proteins in the given pathogen.
"""
pathogenIndex = self._pathogens.setdefault(pathogenName,
len(self._pathogens))
sampleIndex = self._samples.setdefault(sampleName, len(self._samples))
try:
return self._readsFilenames[(pathogenIndex, sampleIndex)]
except KeyError:
reads = Reads()
for proteinMatch in self._proteinGrouper.pathogenNames[
pathogenName][sampleName]['proteins'].values():
for read in self._readsClass(proteinMatch['readsFilename']):
reads.add(read)
saveFilename = join(
proteinMatch['outDir'],
'pathogen-%d-sample-%d.%s' % (pathogenIndex, sampleIndex,
self._format))
reads.filter(removeDuplicatesById=True)
nReads = reads.save(saveFilename, format_=self._format)
# Save the unique read count into self._proteinGrouper
self._proteinGrouper.pathogenNames[
pathogenName][sampleName]['uniqueReadCount'] = nReads
self._readsFilenames[(pathogenIndex, sampleIndex)] = saveFilename
return saveFilename
sys.exit(2)
if variableSites:
toDelete = set()
if args.printSites:
for site, counts in variableSites.items():
if site >= baseOffset:
ref = ((' (ref %s)' %
reference.sequence[site]) if reference else '')
print('%d: %s%s' % (site + 1 - baseOffset, counts, ref),
file=sys.stderr)
else:
toDelete.add(site)
for site in toDelete:
del variableSites[site]
if variableSites:
if args.sitesOnly:
print(','.join(
map(lambda site: str(site + 1 - baseOffset),
sorted(variableSites))))
else:
saveAs = 'fasta' if args.fasta else 'fastq'
reads.filter(keepSites=set(variableSites)).save(sys.stdout, saveAs)
printHeader(variableSites, args, baseOffset)
else:
print('No sites were %svariable (threshold for homogeneity: %.3f).' %
('confirmed ' if args.confirm else '', args.homogeneous),
file=sys.stderr)