def main():
description = """
Given two lists of taxids and one or more hit tables, identify reads that:
(1) have their best hits in taxid list 1
(2) have all other hits in either list
Finally, print out either the hits (that match the target group) for
these reads or just read names (-r). The -F filter limits which hits
are used in part (2) as well as which are printed.
The countMethod (-C) option is not used.
"""
parser = argparse.ArgumentParser(description=description)
add_IO_arguments(parser)
add_taxon_arguments(
parser, defaults={"mapFile": None, "parseStyle": ACCS, "filterPct": -1, "countMethod": "all", "taxdir": None}
)
parser.add_argument(
"-g",
"--targetTaxonGroup",
dest="group1",
default=None,
metavar="TAXON",
action="append",
help="Taxon to identify reads in. Top hits (as defined by "
"--topHitPct) must be in this group. It can be a taxid, "
"a name, or a file listing taxids. Use multiple times to "
"specify a list of organisms. Use -a to specify whether "
"all or at least one of the top hits must match.",
)
parser.add_argument(
"-a",
"--any",
default=False,
action="store_true",
help="If specified, accept reads where any top hit is to an organism "
"in the target taxon/taxa. By default, all top hits must be "
"in the target group.",
)
parser.add_argument(
"-t",
"--topHitPct",
default=0,
type=float,
help="How close(as a percentage to the best score a hit must be "
"to qualify as a top hit. Default is 0, ie must have the best "
"score. Use 100 to get all hits.",
)
parser.add_argument(
"-G",
"--outerTaxonGroup",
dest="group2",
default=None,
metavar="TAXON",
action="append",
help="Broader taxon to limit reads. All hits (use -F to limit "
"these hits) must be in the target group or this group. Again, "
"it can be a taxid, a name, or a file listing taxids. "
"It can also be inkoved multiple times to choose multiple "
"groups.",
)
parser.add_argument(
"-r",
"--reads",
default=False,
action="store_true",
help="Output just read names. By default, print the relevant hit " "lines for each read",
)
# log level and help
add_universal_arguments(parser)
arguments = parser.parse_args()
setup_logging(arguments)
# check args
if arguments.group1 is None:
parser.error("Please use -g to specify a target taxonomic group")
if arguments.taxdir is not None:
taxonomy = readTaxonomy(arguments.taxdir, namesMap=True)
else:
taxonomy = None
group_1_set = get_group_set(arguments.group1, taxonomy)
group_2_set = get_group_set(arguments.group2, taxonomy)
logging.debug("Group 1 has %d entries and 439482 in group1 is %s" % (len(group_1_set), 439482 in group_1_set))
if group_2_set is not None:
logging.debug("Group 2 has %d entries and 439482 in group2 is %s" % (len(group_2_set), 439482 in group_2_set))
# map reads to hits
if arguments.parseStyle == GIS:
keyType = int
else:
keyType = None
accToTaxMap = parseMapFile(arguments.mapFile, valueType=int, keyType=keyType)
# set up some function pointers
global hitRE
hitRE = parsingREs.get(arguments.parseStyle, None)
if arguments.parseStyle == ORGS:
getTaxid = _getOrgTaxid
elif arguments.parseStyle == HITID:
getTaxid = _getHitidTaxid
elif arguments.parseStyle == HITDESC:
getTaxid = _getHitdescTaxid
else:
getTaxid = _getExprTaxid
# for filtering:
filterParams = FilterParams.create_from_arguments(arguments)
logging.debug(repr(filterParams))
# loop over hit tables
for (inhandle, outhandle) in inputIterator(arguments):
readCount = 0
goodReadCount = 0
printCount = 0
# parse file
for (read, hits) in filterM8Stream(inhandle, filterParams, returnLines=False):
readCount += 1
bestScore = 0
hitTaxids = {}
for hit in hits:
score = hit.score
taxids = []
# does this hit have at least one associated taxid in group2?
for taxid in getTaxid(hit, accToTaxMap, taxonomy):
if taxid is None:
break
if group_2_set is not None and taxid not in group_2_set:
break
taxids.append(taxid)
if len(taxids) == 0:
# nothing matched in the wider group
break
hitTaxids[hit] = taxids
# find the top score
if score > bestScore:
bestScore = score
else:
# if we get here, then every hit was in wider taxon list
logging.debug("Checking best hits for %s (top score: %.1f)" % (read, bestScore))
all = True
recognized = []
for hit, taxids in _getBestHitTaxids(hitTaxids, bestScore, arguments.topHitPct):
if _anyTaxidInGroup(taxids, group_1_set):
logging.debug("%s (%r) is in group 1" % (hit, taxids))
recognized.append(hit)
else:
logging.debug("%s (%r) is not in group 1" % (hit, taxids))
all = False
if len(recognized) == 0:
# if none of the best are in our target list, next read
logging.debug("No best hits for %s are in group 1" % (read))
continue
if (not arguments.any) and (not all):
# next read unless user said any or all hits are in list
logging.debug("Not all best hits for %s are in group 1" % (read))
continue
# if we get here, then the read is a match
goodReadCount += 1
if arguments.reads:
logging.debug("Keeping %s" % (read))
outhandle.write(read)
outhandle.write("\n")
else:
logging.debug("Keeping %d hits for %s" % (len(recognized), read))
for hit in sorted(recognized, key=lambda h: (h.score, h.hit)):
outhandle.write(hit.getLine(filterParams))
printCount += 1
if arguments.reads:
logging.info("Printed %d of %d reads" % (goodReadCount, readCount))
else:
logging.info("Printed %d lines for %d of %d reads" % (printCount, goodReadCount, readCount))
def main():
description = __doc__
parser = argparse.ArgumentParser(description)
add_IO_arguments(parser)
parser.add_argument("-l", "--level", dest="levels", default=None,
metavar="LEVEL", action="append",
help=""" Level(s) to collect counts on. Use flag
multiple times to specify multiple levels. If multiple
values given, one table produced for each with rank
name appended to file name. Levels can be an integer
(1-3) for KEGG or SEED levels, any one of 'gene',
'role', 'family',
'ko', or 'ortholog' (which are all synonyms), or
anything not synonymous with 'gene' to
get CAZy groups. Defaults to ortholog/role and
levels 1, 2, and 3 for KEGG and SEED
and gene and group for CAZy and COG.""")
parser.add_argument(
'-s',
'--squash',
dest='splitForLevels',
default=True,
action='store_false',
help="Don't split assignment rows if gene maps to multiple pathways, "
"just squash them into one row using python list syntax")
# format, ortholog heirarchy, and more
kegg.add_path_arguments(parser)
# log level and help
add_universal_arguments(parser)
arguments = parser.parse_args()
setup_logging(arguments)
# Set defaults and check for some conflicts
if arguments.levels is None and arguments.heirarchyFile is None:
# using hit names only
arguments.levels = [None]
else:
if arguments.heirarchyFile is None \
and arguments.heirarchyType != 'cazy':
logging.warn("Type: %s" % (arguments.heirarchyType))
parser.error("Cannot select levels without a heirarchy (ko) file")
if arguments.levels is None:
# set a default
if arguments.heirarchyType is 'kegg':
arguments.levels = ['ko', '1', '2', 'pathway']
if arguments.heirarchyType is 'seed':
arguments.levels = ['role', '1', '2', 'subsystem']
else:
arguments.levels = ['gene', 'group']
try:
# Make sure the level list makes sense
arguments.levels = cleanLevels(arguments.levels)
except Exception as e:
parser.error(str(e))
# map reads to hits
if arguments.mapFile is not None:
if arguments.mapStyle == 'auto':
with open(arguments.mapFile) as f:
firstLine = next(f)
while len(firstLine) == 0 or firstLine[0] == '#':
firstLine = next(f)
if koMapRE.search(firstLine):
arguments.mapStyle = 'kegg'
elif seedMapRE.search(firstLine):
arguments.mapStyle = 'seed'
elif tabMapRE.search(firstLine):
arguments.mapStyle = 'tab'
elif cogMapRE.search(firstLine):
arguments.mapStyle = 'cog'
else:
raise Exception(
"Cannot figure out map type from first line:\n%s" %
(firstLine))
logging.info("Map file seems to be: %s" % (arguments.mapStyle))
if arguments.mapStyle == 'kegg':
valueMap = kegg.parseLinkFile(arguments.mapFile)
elif arguments.mapStyle == 'seed':
valueMap = kegg.parseSeedMap(arguments.mapFile)
elif arguments.mapStyle == 'cog':
valueMap = kegg.parseCogMap(arguments.mapFile)
else:
if arguments.parseStyle == hits.GIS:
keyType = int
else:
keyType = None
valueMap = parseMapFile(
arguments.mapFile,
valueType=None,
keyType=keyType)
if len(valueMap) > 0:
logging.info("Read %d items into map. EG: %s" %
(len(valueMap), next(iter(valueMap.items()))))
else:
logging.warn("Read 0 items into value map!")
else:
valueMap = None
# set up level mapping
levelMappers = [getLevelMapper(l, arguments) for l in arguments.levels]
# parse input files
for (inhandle, outhandle) in inputIterator(arguments):
logging.debug(
"Reading from %s and writing to %s" %
(inhandle, outhandle))
hitMapIter = hits.parseM8FileIter(
inhandle,
valueMap,
arguments.hitTableFormat,
arguments.filterTopPct,
arguments.parseStyle,
arguments.countMethod,
ignoreEmptyHits=arguments.mappedHitsOnly)
if arguments.levels == [None]:
arguments.levels = ['Hit']
outhandle.write("Read\t%s\n" % ('\t'.join(arguments.levels)))
for read, hitIter in hitMapIter:
assignments = []
for hit in hitIter:
logging.debug("Hit: %s" % (hit))
assignment = []
for levelMapper in levelMappers:
assignment.append(levelMapper(hit))
assignments.append(assignment)
logging.debug("Read %s has %d hits" % (read, len(assignments)))
for assignment in assignments:
for assignmentList in handleMultipleMappings(
assignment, arguments):
outhandle.write(
"%s\t%s\n" %
(read, "\t".join(assignmentList)))
def main():
# set up CLI
description = """
Takes a tabular text file and translate a column of KO values into a new
column of KEGG pathways. KO column can have multiple entries per row.
Output column will have multiple entries per pathway cell.
"""
parser = argparse.ArgumentParser(description=description)
util.add_IO_arguments(parser)
parser.add_argument("-l",
"--level",
dest="level",
default="PATHWAY",
metavar="LEVEL",
help=""" Level to collect counts on. Level can
be one of:
NAME, PATHWAY, EC, DEFINITION,
or a level in the CLASS heirachy: 1, 2, or 3
""")
parser.add_argument(
"-f",
"--fill_missing",
dest="fill",
metavar="FILL",
default="No Pathway",
help="Put FILL in column when KO has no pathway assigned. "
"Defaults to 'No Pathway'")
# format, ortholog heirarchy, and more
parser.add_argument("-k",
"--ko_file",
dest="ko_file",
metavar="MAPFILE",
help="Location of kegg ko file")
parser.add_argument("-c",
"--ko_column",
type=int,
default=1,
help="Column number (first column is 1)",
metavar="COLUMN")
parser.add_argument(
"-C",
"--new_column",
type=int,
default=None,
help="Column number to insert new column after. Default is the "
"after the source column. 0=>make it the first column. "
"-1=>make it the last column.",
metavar="COLUMN")
parser.add_argument(
"-L",
"--long_output",
default=False,
action='store_true',
help="Insert new duplicate rows if KO maps to multiple values")
parser.add_argument(
"-H",
"--header",
default=None,
metavar='HEADER',
help="Put HEADER in first row instead of trying to translate")
parser.add_argument("-Q",
"--quotes",
default=False,
action="store_true",
help="Encase translated values in double quotes")
parser.add_argument(
"-s",
"--sep",
dest='sep',
default='\t',
help="""Character separating table cells. Default is tab""")
parser.add_argument(
"-S",
"--ko_sep",
dest='ko_sep',
default=';',
help="""Character separating multiple KO values in iput table
and used to separate multiple values in output column.
Default is ";". Ignored for output if --longOutput
requested""")
# log level and help
util.add_universal_arguments(parser)
arguments = parser.parse_args()
util.setup_logging(arguments)
logging.info("KO mapping from: " + arguments.ko_file)
logging.debug("Fill: '%s'" % (arguments.fill))
translation = kegg.parse_KEGG_file(arguments.ko_file, arguments.level)
# switch to zero indexing
if arguments.new_column:
arguments.new_column -= 1
arguments.ko_column -= 1
for (inhandle, outhandle) in util.inputIterator(arguments):
for new_line in translate_ko_column(
inhandle,
sep=arguments.sep,
ko_sep=arguments.ko_sep,
ko_column=arguments.ko_column,
new_column=arguments.new_column,
translation=translation,
default=arguments.fill,
quotes=arguments.quotes,
header=arguments.header,
long_out=arguments.long_output,
):
outhandle.write(new_line)
def main():
description = __doc__
parser = argparse.ArgumentParser(description=description)
add_IO_arguments(parser)
add_taxon_arguments(parser,
defaults={
'filter_top_pct': 0,
'parseStyle': ACCS,
'countMethod': 'tophit'
},
choices={'countMethod': ('tophit', 'toporg')})
parser.add_argument(
"-P",
"--proportional",
dest="proportional",
default=False,
action="store_true",
help="Assign reads that have multiple equal top hits to taxa such "
"that the overal proportion of taxa is consistent with the "
"unambiguious hits. This is meant for use with the 'toporg' "
"count method.")
parser.add_argument(
"-i",
"--individualFiles",
dest="individual",
default=False,
action="store_true",
help="Use this flag to process files independently. Normally, "
"counts from all files are pooled for making choices.")
add_universal_arguments(parser)
arguments = parser.parse_args()
setup_logging(arguments)
# load necessary maps
params = FilterParams.create_from_arguments(arguments)
if arguments.countMethod == 'toporg':
(taxonomy, hitStringMap) = readMaps(arguments)
wta = not (arguments.proportional)
if len(arguments.input_files) <= 1 or arguments.individual:
# loop over input
for (inhandle, outhandle) in inputIterator(arguments):
logging.debug("Reading from %s and writing to %s" %
(inhandle, outhandle))
m8stream = M8Stream(inhandle)
if arguments.countMethod == 'tophit':
# don't give any taxonomy, just map to accessions for
# redistribution
readHits = redistribute.pickBestHitByAbundance(
m8stream,
filterParams=params,
returnLines=True,
winnerTakeAll=wta,
parseStyle=arguments.parseStyle)
else:
# translate to organism before finding most abundant
readHits = redistribute.pickBestHitByAbundance(
m8stream,
filterParams=params,
returnLines=True,
winnerTakeAll=wta,
taxonomy=taxonomy,
hitStringMap=hitStringMap,
parseStyle=arguments.parseStyle)
for line in readHits:
outhandle.write(line)
else:
# process all files at once
multifile = redistribute.multipleFileWrapper(arguments.input_files)
# Build a map from input file name to output handle
outputMap = {}
for infile_handle in arguments.input_files:
infile_name = infile_handle.name
if arguments.output_file is None:
outputMap[infile_name] = sys.stdout
elif len(arguments.input_files) <= 1:
outputMap[infile_name] = open(arguments.output_file, 'w')
else:
# use outfileName as suffix
if arguments.cwd:
# strip path info first
(infilePath, infileFile) = os.path.split(infile_name)
outfile = "./" + infileFile + arguments.output_file
else:
outfile = infile_name + arguments.output_file
outputMap[infile_name] = open(outfile, 'w')
if arguments.countMethod == 'tophit':
# don't give any taxonomy, just map to accessions for
# redistribution
readHits = redistribute.pickBestHitByAbundance(
multifile,
filterParams=params,
returnLines=False,
winnerTakeAll=wta,
parseStyle=arguments.parseStyle)
else:
# translate to organism before finding most abundant
readHits = redistribute.pickBestHitByAbundance(
multifile,
filterParams=params,
returnLines=False,
winnerTakeAll=wta,
taxonomy=taxonomy,
hitStringMap=hitStringMap,
parseStyle=arguments.parseStyle)
for (read, hit) in readHits:
infile_name, read = read.split("/", 1)
outhandle = outputMap[unquote_plus(infile_name)]
outhandle.write(hit.line.split("/", 1)[1])
if arguments.output_file is not None:
for outhandle in outputMap.values():
outhandle.close()
def main():
description = __doc__
parser = argparse.ArgumentParser(description)
add_IO_arguments(parser)
parser.add_argument("-l",
"--level",
dest="levels",
default=None,
metavar="LEVEL",
action="append",
help=""" Level(s) to collect counts on. Use flag
multiple times to specify multiple levels. If multiple
values given, one table produced for each with rank
name appended to file name. Levels can be an integer
(1-3) for KEGG or SEED levels, any one of 'gene',
'role', 'family',
'ko', or 'ortholog' (which are all synonyms), or
anything not synonymous with 'gene' to
get CAZy groups. Defaults to ortholog/role and
levels 1, 2, and 3 for KEGG and SEED
and gene and group for CAZy and COG.""")
parser.add_argument(
'-S',
'--squash',
dest='splitForLevels',
default=True,
action='store_false',
help="Don't split assignment rows if gene maps to multiple pathways, "
"just squash them into one row using python list syntax")
# format, ortholog heirarchy, and more
kegg.add_path_arguments(parser)
# log level and help
add_universal_arguments(parser)
arguments = parser.parse_args()
setup_logging(arguments)
# Set defaults and check for some conflicts
if arguments.levels is None and arguments.heirarchyFile is None:
# using hit names only
arguments.levels = [None]
else:
if arguments.heirarchyFile is None \
and arguments.heirarchyType != 'cazy':
logging.warn("Type: %s" % (arguments.heirarchyType))
parser.error("Cannot select levels without a heirarchy (ko) file")
if arguments.levels is None:
# set a default
if arguments.heirarchyType is 'kegg':
arguments.levels = ['ko', '1', '2', 'pathway']
if arguments.heirarchyType is 'seed':
arguments.levels = ['role', '1', '2', 'subsystem']
else:
arguments.levels = ['gene', 'group']
try:
# Make sure the level list makes sense
arguments.levels = cleanLevels(arguments.levels)
except Exception as e:
parser.error(str(e))
# map reads to hits
if arguments.mapFile is not None:
if arguments.mapStyle == 'auto':
with open(arguments.mapFile) as f:
firstLine = next(f)
while len(firstLine) == 0 or firstLine[0] == '#':
firstLine = next(f)
if koMapRE.search(firstLine):
arguments.mapStyle = 'kegg'
elif seedMapRE.search(firstLine):
arguments.mapStyle = 'seed'
elif tabMapRE.search(firstLine):
arguments.mapStyle = 'tab'
elif cogMapRE.search(firstLine):
arguments.mapStyle = 'cog'
else:
raise Exception(
"Cannot figure out map type from first line:\n%s" %
(firstLine))
logging.info("Map file seems to be: %s" % (arguments.mapStyle))
if arguments.mapStyle == 'kegg':
valueMap = kegg.parseLinkFile(arguments.mapFile)
elif arguments.mapStyle == 'seed':
valueMap = kegg.parseSeedMap(arguments.mapFile)
elif arguments.mapStyle == 'cog':
valueMap = kegg.parseCogMap(arguments.mapFile)
else:
if arguments.parseStyle == hits.GIS:
keyType = int
else:
keyType = None
valueMap = parseMapFile(arguments.mapFile,
valueType=None,
valueDelim=arguments.tab_map_delim,
keyType=keyType)
if len(valueMap) > 0:
logging.info("Read %d items into map. EG: %s" %
(len(valueMap), next(iter(valueMap.items()))))
else:
logging.warn("Read 0 items into value map!")
else:
valueMap = None
# set up level mapping
levelMappers = [getLevelMapper(lvl, arguments) for lvl in arguments.levels]
# parse input files
for (inhandle, outhandle) in inputIterator(arguments):
logging.debug("Reading from %s and writing to %s" %
(inhandle, outhandle))
hitMapIter = hits.parseM8FileIter(
inhandle,
valueMap,
hits.FilterParams.create_from_arguments(arguments),
arguments.parseStyle,
arguments.countMethod,
ignoreEmptyHits=arguments.mappedHitsOnly)
if arguments.levels == [None]:
arguments.levels = ['Hit']
outhandle.write("Read\t%s\n" % ('\t'.join(arguments.levels)))
for read, hitIter in hitMapIter:
assignments = []
for hit in hitIter:
logging.debug("Hit: %s" % (hit))
assignment = []
for levelMapper in levelMappers:
assignment.append(levelMapper(hit))
assignments.append(assignment)
logging.debug("Read %s has %d hits" % (read, len(assignments)))
for assignment in assignments:
for assignmentList in handleMultipleMappings(
assignment, arguments):
outhandle.write("%s\t%s\n" %
(read, "\t".join(assignmentList)))
def main():
description = """
Given two lists of taxids and one or more hit tables, identify reads that:
(1) have their best hits in taxid list 1
(2) have all other hits in either list
Finally, print out either the hits (that match the target group) for
these reads or just read names (-r). The -F filter limits which hits
are used in part (2) as well as which are printed.
The countMethod (-C) option is not used.
"""
parser = argparse.ArgumentParser(description=description)
add_IO_arguments(parser)
add_taxon_arguments(
parser,
defaults={
'mapFile': None,
'parseStyle': ACCS,
'filter_top_pct': -1,
'countMethod': 'all',
'taxdir': None})
parser.add_argument(
"-g",
"--targetTaxonGroup",
dest="group1",
default=None,
metavar="TAXON",
action='append',
help="Taxon to identify reads in. Top hits (as defined by "
"--topHitPct) must be in this group. It can be a taxid, "
"a name, or a file listing taxids. Use multiple times to "
"specify a list of organisms. Use -a to specify whether "
"all or at least one of the top hits must match.")
parser.add_argument(
"-a",
"--any",
default=False,
action="store_true",
help="If specified, accept reads where any top hit is to an organism "
"in the target taxon/taxa. By default, all top hits must be "
"in the target group.")
parser.add_argument(
'-t',
'--topHitPct',
default=0,
type=float,
help="How close(as a percentage to the best score a hit must be "
"to qualify as a top hit. Default is 0, ie must have the best "
"score. Use 100 to get all hits.")
parser.add_argument(
"-G",
"--outerTaxonGroup",
dest="group2",
default=None,
metavar="TAXON",
action="append",
help="Broader taxon to limit reads. All hits (use -F to limit "
"these hits) must be in the target group or this group. Again, "
"it can be a taxid, a name, or a file listing taxids. "
"It can also be inkoved multiple times to choose multiple "
"groups.")
parser.add_argument(
'-r',
'--reads',
default=False,
action="store_true",
help="Output just read names. By default, print the relevant hit "
"lines for each read")
# log level and help
add_universal_arguments(parser)
arguments = parser.parse_args()
setup_logging(arguments)
# check args
if arguments.group1 is None:
parser.error("Please use -g to specify a target taxonomic group")
if arguments.taxdir is not None:
taxonomy = readTaxonomy(arguments.taxdir, namesMap=True)
else:
taxonomy = None
group_1_set = get_group_set(arguments.group1, taxonomy)
group_2_set = get_group_set(arguments.group2, taxonomy)
logging.debug(
"Group 1 has %d entries and 439482 in group1 is %s" %
(len(group_1_set), 439482 in group_1_set))
if group_2_set is not None:
logging.debug(
"Group 2 has %d entries and 439482 in group2 is %s" %
(len(group_2_set), 439482 in group_2_set))
# map reads to hits
if arguments.parseStyle == GIS:
keyType = int
else:
keyType = None
accToTaxMap = parseMapFile(
arguments.mapFile,
valueType=int,
keyType=keyType)
# set up some function pointers
global hitRE
hitRE = parsingREs.get(arguments.parseStyle, None)
if arguments.parseStyle == ORGS:
getTaxid = _getOrgTaxid
elif arguments.parseStyle == HITID:
getTaxid = _getHitidTaxid
elif arguments.parseStyle == HITDESC:
getTaxid = _getHitdescTaxid
else:
getTaxid = _getExprTaxid
# for filtering:
filterParams = FilterParams.create_from_arguments(arguments)
logging.debug(repr(filterParams))
# loop over hit tables
for (inhandle, outhandle) in inputIterator(arguments):
readCount = 0
goodReadCount = 0
printCount = 0
# parse file
for (
read,
hits) in filterM8Stream(
inhandle,
filterParams,
return_lines=False):
readCount += 1
bestScore = 0
hitTaxids = {}
for hit in hits:
score = hit.score
taxids = []
# does this hit have at least one associated taxid in group2?
for taxid in getTaxid(hit, accToTaxMap, taxonomy):
if taxid is None:
break
if group_2_set is not None and taxid not in group_2_set:
break
taxids.append(taxid)
if len(taxids) == 0:
# nothing matched in the wider group
break
hitTaxids[hit] = taxids
# find the top score
if score > bestScore:
bestScore = score
else:
# if we get here, then every hit was in wider taxon list
logging.debug(
"Checking best hits for %s (top score: %.1f)" %
(read, bestScore))
all = True
recognized = []
for hit, taxids in _getBestHitTaxids(
hitTaxids, bestScore, arguments.topHitPct):
if _anyTaxidInGroup(taxids, group_1_set):
logging.debug("%s (%r) is in group 1" % (hit, taxids))
recognized.append(hit)
else:
logging.debug(
"%s (%r) is not in group 1" %
(hit, taxids))
all = False
if len(recognized) == 0:
# if none of the best are in our target list, next read
logging.debug(
"No best hits for %s are in group 1" %
(read))
continue
if (not arguments.any) and (not all):
# next read unless user said any or all hits are in list
logging.debug(
"Not all best hits for %s are in group 1" %
(read))
continue
# if we get here, then the read is a match
goodReadCount += 1
if arguments.reads:
logging.debug("Keeping %s" % (read))
outhandle.write(read)
outhandle.write('\n')
else:
logging.debug(
"Keeping %d hits for %s" %
(len(recognized), read))
for hit in sorted(
recognized,
key=lambda h: (
h.score,
h.hit)):
outhandle.write(hit.getLine(filterParams))
printCount += 1
if arguments.reads:
logging.info("Printed %d of %d reads" % (goodReadCount, readCount))
else:
logging.info(
"Printed %d lines for %d of %d reads" %
(printCount, goodReadCount, readCount))
def main():
""" The CLI """
description = """
Takes a hit table (reads searched against a database) and assigns
each read to a taxon. Hit table may be specified with -i or piped to STDIN.
Notes:
* Specifying a top score precent (-F) will force hits to be sorted
by score within each read. However, it is assumed that the hits in
the input table(s) are already grouped by read. This program does
not attempt to sort the entire input.
"""
parser = argparse.ArgumentParser(description)
util.add_IO_arguments(parser)
parser.add_argument("-T", "--taxids", default=False, action="store_true",
help="Output taxids instead of names")
edlhits.add_taxon_arguments(parser)
parser.add_argument(
"-r",
"--rank",
dest="rank",
default=None,
metavar="RANK",
help=" Rank to collect counts on. Defaults to None (whatever "
"the annotation was). Corresponds to rank names in nodes.dmp. "
"To see list run: 'cut -f5 nodes.dmp | uniq | sort | uniq' in "
"ncbi tax dir")
parser.add_argument(
"-R",
"--printRank",
dest="printRanks",
action="append",
help="Include indeicated rank(s) in lineage of printed taxa. "
"Will be ignored if beyond the rank of the taxa "
"(IE We can't include species if the taxon being counted "
"is genus)")
parser.add_argument(
"--no-header",
dest="no_header",
default=False,
action='store_true',
help="do not write header line")
util.add_universal_arguments(parser)
arguments = parser.parse_args()
util.setup_logging(arguments)
logging.debug("Parsing style is: %s", arguments.parseStyle)
# Handle the case where Galaxy tries to set None as a string
arguments.printRanks = util.checkNoneOption(arguments.printRanks)
# check arguments
if arguments.taxids and arguments.taxdir is None:
parser.error("Only use -T when a taxonomy is specified")
if arguments.rank is not None and arguments.taxdir is None:
parser.error(
"Please supply NCBI phylogeny(-n) if specifying a rank(-r).")
if arguments.printRanks is not None and arguments.taxdir is None:
parser.error(
"Please supply NCBI phylogeny(-n) if specifying a rank(-R).")
if arguments.rank is not None:
if arguments.rank == 'domain':
logging.warning('translating domain to superkingdom')
arguments.rank = 'superkingdom'
if arguments.rank not in ranks:
parser.error("Unknown rank: %s" % (arguments.rank))
try:
# Make sure the rank lists make sense
if arguments.printRanks is not None:
arguments.printRanks = cleanRanks(arguments.printRanks)
except Exception as exc:
parser.error(str(exc))
# load necessary maps
(taxonomy, value_map) = edlhits.readMaps(arguments)
# loop over inputs
for (inhandle, outhandle) in util.inputIterator(arguments):
logging.debug(
"Reading from %s and writing to %s",
inhandle, outhandle)
hit_iter = edlhits.parseM8FileIter(
inhandle,
value_map,
edlhits.FilterParams.create_from_arguments(arguments),
arguments.parseStyle,
arguments.countMethod,
taxonomy=taxonomy,
rank=arguments.rank)
##
# print output
# choose output method
if arguments.taxids:
hit_header = 'taxid'
printer = taxid_printer
else:
if arguments.printRanks is None:
hit_header = 'Hit(s)'
printer = default_printer
else:
hit_header = '\t'.join(arguments.printRanks)
def printer(read, hits):
" Inline function to reduce number of arguments "
return tax_table_printer(read,
hits,
arguments.rank,
arguments.printRanks)
# loop over reads
if not arguments.no_header:
outhandle.write("Read\t{}\n".format(hit_header))
for (read, hits) in hit_iter:
outhandle.write(printer(read, hits))
def main():
description = __doc__
parser = argparse.ArgumentParser(description=description)
add_IO_arguments(parser)
add_taxon_arguments(
parser,
defaults={
'filter_top_pct': 0,
'parseStyle': ACCS,
'countMethod': 'tophit'},
choices={
'countMethod': (
'tophit',
'toporg')})
parser.add_argument(
"-P",
"--proportional",
dest="proportional",
default=False,
action="store_true",
help="Assign reads that have multiple equal top hits to taxa such "
"that the overal proportion of taxa is consistent with the "
"unambiguious hits. This is meant for use with the 'toporg' "
"count method.")
parser.add_argument(
"-i",
"--individualFiles",
dest="individual",
default=False,
action="store_true",
help="Use this flag to process files independently. Normally, "
"counts from all files are pooled for making choices.")
add_universal_arguments(parser)
arguments = parser.parse_args()
setup_logging(arguments)
# load necessary maps
params = FilterParams.create_from_arguments(arguments)
if arguments.countMethod == 'toporg':
(taxonomy, hitStringMap) = readMaps(arguments)
wta = not(arguments.proportional)
if len(arguments.input_files) <= 1 or arguments.individual:
# loop over input
for (inhandle, outhandle) in inputIterator(arguments):
logging.debug(
"Reading from %s and writing to %s" %
(inhandle, outhandle))
m8stream = M8Stream(inhandle)
if arguments.countMethod == 'tophit':
# don't give any taxonomy, just map to accessions for
# redistribution
readHits = redistribute.pickBestHitByAbundance(
m8stream,
filterParams=params,
returnLines=True,
winnerTakeAll=wta,
parseStyle=arguments.parseStyle)
else:
# translate to organism before finding most abundant
readHits = redistribute.pickBestHitByAbundance(
m8stream,
filterParams=params,
returnLines=True,
winnerTakeAll=wta,
taxonomy=taxonomy,
hitStringMap=hitStringMap,
parseStyle=arguments.parseStyle)
for line in readHits:
outhandle.write(line)
else:
# process all files at once
multifile = redistribute.multipleFileWrapper(arguments.input_files)
# Build a map from input file name to output handle
outputMap = {}
for infile_handle in arguments.input_files:
infile_name = infile_handle.name
if arguments.output_file is None:
outputMap[infile_name] = sys.stdout
elif len(arguments.input_files) <= 1:
outputMap[infile_name] = open(arguments.output_file, 'w')
else:
# use outfileName as suffix
if arguments.cwd:
# strip path info first
(infilePath, infileFile) = os.path.split(infile_name)
outfile = "./" + infileFile + arguments.output_file
else:
outfile = infile_name + arguments.output_file
outputMap[infile_name] = open(outfile, 'w')
if arguments.countMethod == 'tophit':
# don't give any taxonomy, just map to accessions for
# redistribution
readHits = redistribute.pickBestHitByAbundance(
multifile,
filterParams=params,
returnLines=False,
winnerTakeAll=wta,
parseStyle=arguments.parseStyle)
else:
# translate to organism before finding most abundant
readHits = redistribute.pickBestHitByAbundance(
multifile,
filterParams=params,
returnLines=False,
winnerTakeAll=wta,
taxonomy=taxonomy,
hitStringMap=hitStringMap,
parseStyle=arguments.parseStyle)
for (read, hit) in readHits:
infile_name, read = read.split("/", 1)
outhandle = outputMap[unquote_plus(infile_name)]
outhandle.write(hit.line.split("/", 1)[1])
if arguments.output_file is not None:
for outhandle in outputMap.values():
outhandle.close()
