def main(args=None):
if args is None:
args = sys.argv[:]
user_options = Options(prog="sequana")
# If --help or no options provided, show the help
if len(args) == 1:
user_options.parse_args(["prog", "--help"])
else:
options = user_options.parse_args(args[1:])
logger.level = options.level
if options.update_taxonomy is True:
from sequana.taxonomy import Taxonomy
tax = Taxonomy()
from sequana import sequana_config_path as cfg
logger.info(
"Will overwrite the local database taxonomy.dat in {}".format(cfg))
tax.download_taxonomic_file(overwrite=True)
sys.exit(0)
# We put the import here to make the --help faster
from sequana import KrakenPipeline
from sequana.kraken import KrakenSequential
devtools = DevTools()
if options.download:
from sequana import KrakenDownload
kd = KrakenDownload()
kd.download(options.download)
sys.exit()
fastq = []
if options.file1:
devtools.check_exists(options.file1)
fastq.append(options.file1)
if options.file2:
devtools.check_exists(options.file2)
fastq.append(options.file2)
from sequana import sequana_config_path as scfg
if options.databases is None:
logger.critical("You must provide a database")
sys.exit(1)
databases = []
for database in options.databases:
if database == "toydb":
database = "kraken_toydb"
elif database == "minikraken":
database = "minikraken_20141208"
if os.path.exists(scfg + os.sep + database): # in Sequana path
databases.append(scfg + os.sep + database)
elif os.path.exists(database): # local database
databases.append(database)
else:
msg = "Invalid database name (%s). Neither found locally "
msg += "or in the sequana path %s; Use the --download option"
raise ValueError(msg % (database, scfg))
output_directory = options.directory + os.sep + "kraken"
devtools.mkdirs(output_directory)
# if there is only one database, use the pipeline else KrakenHierarchical
_pathto = lambda x: "{}/kraken/{}".format(options.directory, x) if x else x
if len(databases) == 1:
logger.info("Using 1 database")
k = KrakenPipeline(fastq,
databases[0],
threads=options.thread,
output_directory=output_directory,
confidence=options.confidence)
k.run(output_filename_classified=_pathto(options.classified_out),
output_filename_unclassified=_pathto(options.unclassified_out))
else:
logger.info("Using %s databases" % len(databases))
k = KrakenSequential(fastq,
databases,
threads=options.thread,
output_directory=output_directory + os.sep,
force=True,
keep_temp_files=options.keep_temp_files,
output_filename_unclassified=_pathto(
options.unclassified_out),
confidence=options.confidence)
k.run(output_prefix="kraken")
# This statements sets the directory where HTML will be saved
from sequana.utils import config
config.output_dir = options.directory
# output_directory first argument: the directory where to find the data
# output_filename is relative to the config.output_dir defined above
kk = KrakenModule(output_directory, output_filename="summary.html")
logger.info("Open ./%s/summary.html" % options.directory)
logger.info("or ./%s/kraken/kraken.html" % options.directory)
if options.html is True:
ss.onweb()
def main(args=None):
if args is None:
args = sys.argv[:]
user_options = Options(prog="sequana")
# If --help or no options provided, show the help
if len(args) == 1:
user_options.parse_args(["prog", "--help"])
else:
options = user_options.parse_args(args[1:])
logger.level = options.level
# We put the import here to make the --help faster
from sequana import KrakenPipeline
from sequana.kraken import KrakenHierarchical
devtools = DevTools()
if options.download:
from sequana import KrakenDownload
kd = KrakenDownload()
kd.download(options.download)
sys.exit()
fastq = []
if options.file1:
devtools.check_exists(options.file1)
fastq.append(options.file1)
if options.file2:
devtools.check_exists(options.file2)
fastq.append(options.file2)
from sequana import sequana_config_path as scfg
if options.databases is None:
_log.critical("You must provide a database")
sys.exit(1)
databases = []
for database in options.databases:
if database == "toydb":
database = "kraken_toydb"
elif database == "minikraken":
database = "minikraken_20141208"
if os.path.exists(scfg + os.sep + database): # in Sequana path
databases.append(scfg + os.sep + database)
elif os.path.exists(database): # local database
databases.append(database)
else:
msg = "Invalid database name (%s). Neither found locally "
msg += "or in the sequana path %s; Use the --download option"
raise ValueError(msg % (database, scfg))
output_directory = options.directory + os.sep + "kraken"
devtools.mkdirs(output_directory)
# if there is only one database, use the pipeline else KrakenHierarchical
if len(databases) == 1:
_log.info("Using 1 database")
k = KrakenPipeline(fastq, databases[0], threads=options.thread,
output_directory=output_directory)
_pathto = lambda x: "{}/kraken/{}".format(options.directory, x) if x else x
k.run(output_filename_classified=_pathto(options.classified_out),
output_filename_unclassified=_pathto(options.unclassified_out))
else:
_log.info("Using %s databases" % len(databases))
k = KrakenHierarchical(fastq, databases, threads=options.thread,
output_directory=output_directory+os.sep, force=True,
keep_temp_files=options.keep_temp_files)
k.run(output_prefix="kraken")
# This statements sets the directory where HTML will be saved
from sequana.utils import config
config.output_dir = options.directory
# output_directory first argument: the directory where to find the data
# output_filename is relative to the config.output_dir defined above
kk = KrakenModule(output_directory, output_filename="summary.html")
_log.info("Open ./%s/summary.html" % options.directory)
_log.info("or ./%s/kraken/kraken.html" % options.directory)
if options.html is True:
ss.onweb()
class KrakenAnalysis(object):
"""Run kraken on a set of FastQ files
In order to run a Kraken analysis, we firtst need a local database.
We provide a Toy example. The ToyDB is downloadable as follows ( you will
need to run the following code only once)::
from sequana import KrakenDownload
kd = KrakenDownload()
kd.download_kraken_toydb()
.. seealso:: :class:`KrakenDownload` for more database and
:class:`sequana.kraken_builder.KrakenBuilder` to build your own
databases
The path to the database is required to run the analysis. It has been
stored in the directory ./config/sequana/kraken_toydb under Linux platforms
The following code should be platform independent::
import os
from sequana import sequana_config_path
database = sequana_config_path + os.sep + "kraken_toydb")
Finally, we can run the analysis on the toy data set::
from sequana import sequana_data
data = sequana_data("Hm2_GTGAAA_L005_R1_001.fastq.gz", "data")
ka = KrakenAnalysis(data, database=database)
ka.run()
This creates a file named *kraken.out*. It can be interpreted with
:class:`KrakenResults`
"""
def __init__(self, fastq, database, threads=4):
""".. rubric:: Constructor
:param fastq: either a fastq filename or a list of 2 fastq filenames
:param database: the path to a valid Kraken database
:param threads: number of threads to be used by Kraken
:param output: output filename of the Krona HTML page
:param return:
"""
self._devtools = DevTools()
self._devtools.check_exists(database)
self.database = database
self.threads = threads
# Fastq input
if isinstance(fastq, str):
self.paired = False
self.fastq = [fastq]
elif isinstance(fastq, list):
if len(fastq) == 2:
self.paired = True
else:
self.paired = False
self.fastq = fastq
else:
raise ValueError(
"Expected a fastq filename or list of 2 fastq filenames")
for this in self.fastq:
self._devtools.check_exists(database)
def run(self,
output_filename=None,
output_filename_classified=None,
output_filename_unclassified=None,
only_classified_output=False):
"""Performs the kraken analysis
:param str output_filename: if not provided, a temporary file is used
and stored in :attr:`kraken_output`.
:param str output_filename_classified: not compressed
:param str output_filename_unclassified: not compressed
"""
if output_filename is None:
self.kraken_output = TempFile().name
else:
self.kraken_output = output_filename
params = {
"database": self.database,
"thread": self.threads,
"file1": self.fastq[0],
"kraken_output": self.kraken_output,
"output_filename_unclassified": output_filename_unclassified,
"output_filename_classified": output_filename_classified,
}
if self.paired:
params["file2"] = self.fastq[1]
command = "kraken -db %(database)s %(file1)s "
if self.paired:
command += " %(file2)s --paired"
command += " --threads %(thread)s --out %(kraken_output)s"
if output_filename_unclassified:
command += " --unclassified-out %(output_filename_unclassified)s "
if only_classified_output is True:
command += " --only-classified-output"
if output_filename_classified:
command += " --classified-out %(output_filename_classified)s "
command = command % params
# Somehow there is an error using easydev.execute with pigz
from snakemake import shell
shell(command)
class KrakenAnalysis(object):
"""Run kraken on a set of FastQ files
In order to run a Kraken analysis, we firtst need a local database.
We provide a Toy example. The ToyDB is downloadable as follows ( you will
need to run the following code only once)::
from sequana import KrakenDownload
kd = KrakenDownload()
kd.download_kraken_toydb()
.. seealso:: :class:`KrakenDownload` for more database and
:class:`sequana.kraken_builder.KrakenBuilder` to build your own
databases
The path to the database is required to run the analysis. It has been
stored in the directory ./config/sequana/kraken_toydb under Linux platforms
The following code should be platform independent::
import os
from sequana import sequana_config_path
database = sequana_config_path + os.sep + "kraken_toydb")
Finally, we can run the analysis on the toy data set::
from sequana import sequana_data
data = sequana_data("Hm2_GTGAAA_L005_R1_001.fastq.gz", "data")
ka = KrakenAnalysis(data, database=database)
ka.run()
This creates a file named *kraken.out*. It can be interpreted with
:class:`KrakenResults`
"""
def __init__(self, fastq, database, threads=4 ):
""".. rubric:: Constructor
:param fastq: either a fastq filename or a list of 2 fastq filenames
:param database: the path to a valid Kraken database
:param threads: number of threads to be used by Kraken
:param output: output filename of the Krona HTML page
:param return:
"""
self._devtools = DevTools()
self._devtools.check_exists(database)
self.database = database
self.threads = threads
# Fastq input
if isinstance(fastq, str):
self.paired = False
self.fastq = [fastq]
elif isinstance(fastq, list):
if len(fastq) == 2:
self.paired = True
else:
self.paired = False
self.fastq = fastq
else:
raise ValueError("Expected a fastq filename or list of 2 fastq filenames")
for this in self.fastq:
self._devtools.check_exists(database)
def run(self, output_filename=None, output_filename_classified=None,
output_filename_unclassified=None, only_classified_output=False):
"""Performs the kraken analysis
:param str output_filename: if not provided, a temporary file is used
and stored in :attr:`kraken_output`.
:param str output_filename_classified: not compressed
:param str output_filename_unclassified: not compressed
"""
if output_filename is None:
self.kraken_output = TempFile().name
else:
self.kraken_output = output_filename
params = {
"database": self.database,
"thread": self.threads,
"file1": self.fastq[0],
"kraken_output": self.kraken_output,
"output_filename_unclassified": output_filename_unclassified,
"output_filename_classified": output_filename_classified,
}
if self.paired:
params["file2"] = self.fastq[1]
command = "kraken -db %(database)s %(file1)s "
if self.paired:
command += " %(file2)s --paired"
command += " --threads %(thread)s --output %(kraken_output)s "
command += " --out-fmt legacy"
if output_filename_unclassified:
command += " --unclassified-out %(output_filename_unclassified)s "
if only_classified_output is True:
command += " --only-classified-output"
if output_filename_classified:
command += " --classified-out %(output_filename_classified)s "
command = command % params
# Somehow there is an error using easydev.execute with pigz
from snakemake import shell
shell(command)
