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backuplara_launcher_31Julio.py
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backuplara_launcher_31Julio.py
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#! /usr/bin/env python
# THINGS TO IMPROVE:
# THINGS TO FIX:
# if bowtie2 directly with cufflinks or express (directly from assembly) >>> folder created in .cache/tmp
# >>> this has been fixed but clumsy in bowtie2.cmd
# THINGS TO INSTALL:
#CDHITEST
# THINGS TO IMPROVE:
# in bowtie 2 command, check the output files names (the first linesof the cmd)
# remove env variables (not used the same way anymore) <<< not sure about that
# Make better the import of the parameters (without having to delete the other entries in sort_parameters)
# THINGS TO VERIFY (TESTING PARAMETERS NOT CORRECT FOR REAL USE)
# input files (reads)
#-------------------------------------------------------------------------------
import logging
import logging.handlers
import sys
import os
import getopt
import mimetypes
import time
from lib import submiting_jobs as sj
from lib import soft_data
from lib import config
from lib import run_config
#from lib import common_fun
#-------------------------------------------------------------------------------
def configLog():
# get logger
logger = logging.getLogger()
# create file handler
ch = logging.handlers.RotatingFileHandler( config.LOGFILE, mode='a', maxBytes=config.LOGFILEBYTES, backupCount=5 )
ch.setLevel( logging.DEBUG )
# create formatter
formatter = logging.Formatter(
fmt='%(asctime)s -%(levelname)s- %(message)s',
datefmt='%Y%m%d %H:%M:%S' )
# add formatter to ch
ch.setFormatter( formatter )
# add ch to logger
logger.addHandler( ch )
logging.captureWarnings( True )
#-------------------------------------------------------------------------------
def checkIfCommandLine():
""" Check if command line or webserver version.
For command line: edit run_config in lib and launch ./pipe_launcher -c """
try:
opts, args = getopt.getopt(sys.argv[1:], "c")
except getopt.GetoptError as err:
print str(err)
sys.exit(2)
for o, a in opts:
if o == "-c":
return True
else:
return False
#-------------------------------------------------------------------------------
def setUidJid(COMMAND_MODE):
if COMMAND_MODE:
print "Launching in command line mode"
REALUSER = run_config.REALUSER
job_num = run_config.JOB_NUM
para_dict = run_config.para_dict
DEBUG = run_config.DEBUG
# common_fun.check_inputs_format(para_dict)
else: # if run by webserver
print "Launched by the webserver"
DEBUG = False
REALUSER, para_dict = sj.get_parameters(sys.argv[1],sys.argv[2])
job_num = sys.argv[-1]
return REALUSER, job_num, para_dict, DEBUG
#-------------------------------------------------------------------------------
def setPaths():
OUT_FOLDER = config.OUT_FOLDER + REALUSER + "/jobs/Job_" + job_num + "/"
DATA_FOLDER = config.OUT_FOLDER + REALUSER + "/data/"
folders_dict = dict(OUT_FOLDER = OUT_FOLDER,
DATA_FOLDER = DATA_FOLDER,
CACHE_PATH = OUT_FOLDER + ".cache/",
CLEANING_FOLDER = OUT_FOLDER + "CLEANING/",
STAT_FOLDER = OUT_FOLDER + "STAT/",
ASSEMBLY_MAPPING_FOLDER = OUT_FOLDER + "ASSEMBLY_MAPPING/",
IDENTIFICATION_FOLDER = OUT_FOLDER + "IDENTIFICATION/",
EXPRESSION_FOLDER = OUT_FOLDER + "EXPRESSION/",
PIPE_PATH = config.PIPE_PATH,
PY_BIOLIB_PATH = config.PY_BIOLIB_PATH,
COMMAND_PATH = config.COMMAND_PATH,
DOCKER_CLEANING= config.DOCKER_CLEANING,
DOCKER_ASSEMBLY= config.DOCKER_ASSEMBLY,
DOCKER_IDENTIFY= config.DOCKER_IDENTIFY)
COMMAND_PATH = config.COMMAND_PATH
BLAST_DB_FOLDER = config.BLAST_DB_FOLDER
HMMER_PROFILE_FOLDER = config.HMMER_PROFILE_FOLDER
return folders_dict, COMMAND_PATH, BLAST_DB_FOLDER, HMMER_PROFILE_FOLDER
#-------------------------------------------------------------------------------
def makeOutputFolders(folders_dict):
try:
os.makedirs(folders_dict["OUT_FOLDER"])
os.makedirs(folders_dict["CACHE_PATH"])
os.mkdir(folders_dict["CACHE_PATH"] + "tmp")
os.mkdir(folders_dict["STAT_FOLDER"])
except Exception as e:
logging.error(e)
sys.exit()
#-------------------------------------------------------------------------------
def getInput(para_dict):
input_dict = sj.sort_parameters(para_dict)
READS_FILES = input_dict["reads_files"]
READS_FILES_COUNT = len(READS_FILES)
BLATN_CUSTOM_READS = input_dict["blatn_reads"]
BLATN_CUSTOM_ASS = input_dict["blatn_ass"]
BLATX_CUSTOM_ASS = input_dict["blatx_ass"]
HMMER_CUSTOM_DB = input_dict["hmm_custom_db"]
return input_dict, READS_FILES, READS_FILES_COUNT, BLATN_CUSTOM_READS,BLATN_CUSTOM_ASS, BLATX_CUSTOM_ASS, HMMER_CUSTOM_DB
#-------------------------------------------------------------------------------
def setBashEnv(input_dict, folders_dict):
env = sj.set_environment(input_dict, folders_dict)
env["MINIMAL_OUTPUT"]=config.MINIMAL_OUTPUT
# Add for MPIBLAST:
#env["BLASTMAT"]="/mnt/seq_dbs/matrices"
#env["MPIBLAST_SHARED"]="/mnt/seq_dbs/nr"
#env["MPIBLAST_LOCAL"]=folders_dict["IDENTIFICATION_FOLDER"] + ""
return env
#-------------------------------------------------------------------------------
def checkIfCompressedReads(folders_dict, READS_FILES):
new_READS_FILES = []
with open(folders_dict["OUT_FOLDER"] + ".tmp1.txt", "a") as f:
files_to_unzip = []
for rf in READS_FILES:
raw = rf
rf = rf.split( os.extsep, 2 )
fname = ".".join( rf[:2] )
ext = rf[-1]
# Check extension:
if ext in ["gz","tar.gz"]:
f.write("File: {0} is set for extraction\n".format(raw))
files_to_unzip.append(raw)
new_READS_FILES.append(fname)
else:
f.write("""File: {0} doesn't seem to be a compressed file,
or his extension is not recognized, so it will be considered
as a 'directly usable' file\n""".format(raw))
new_READS_FILES.append(raw)
return new_READS_FILES, files_to_unzip
#-------------------------------------------------------------------------------
def extract(files_to_unzip, OUT_FOLDER, COMMAND_PATH, dep):
env["FILES_TO_UNZIP"] = "'" + " ".join(files_to_unzip) + "'"
job_id = sj.make_and_submit_job(OUT_FOLDER,
COMMAND_PATH + "extract2.cmd",
"extract", 1,
1, "12:00:00","", env)
# slurm_ids.append(job_id)
dep.append(job_id)
return dep
#-------------------------------------------------------------------------------
class TrufaJob():
"""
To define better names
HERE:
jobfolder is for the whole Job, composed of TrufaJobs e.g; OUT_FOLDER
outfolder is the outfolder of the TrufaJob: STAT_FOLDER/fastqc_report
"""
def __init__(self, name, command, dep, jobfolder, ntasks, ncpus, tlim, env, outfolder=None):
self.name = name
self.command_path = config.COMMAND_PATH + command
self.dep = dep
self.jobfolder = jobfolder
self.outfolder = outfolder
self.ntasks = ntasks
self.ncpus = ncpus
self.tlim = tlim
self.env = env
def makeOutFolder(self):
if self.outfolder:
if not os.path.exists(self.outfolder):
os.makedirs(self.outfolder)
else:
print self.name
print self.outfolder + " already exists: not created (it's fine)."
def script(self):
sj.make_script(self.jobfolder,
self.command_path,
self.name,
self.ntasks,
self.ncpus,
self.tlim,
self.dep,
self.env,
DEBUG)
def submit(self):
job_id = sj.make_and_submit_job(self.jobfolder,
self.command_path,
self.name,
self.ntasks,
self.ncpus,
self.tlim,
self.dep,
self.env,
DEBUG)
return job_id
#-------------------------------------------------------------------------------
def prepareAndSubmit( jobname, cmd, dep, jobfolder, ntasks, cpus, tlim, env, outfolder=None):
"""
Prepare the outfolders and submit a TrufaJob
"""
try:
job = TrufaJob( jobname, cmd, dep, jobfolder, ntasks, cpus, tlim, env, outfolder)
job.makeOutFolder()
slurm_id = job.submit()
except Exception as e:
print e
print "Entra en la excepcion"
logging.error(e)
sys.exit()
return slurm_id
#------------------------------------------------------------------------------
def prepareScript( jobname, cmd, dep, jobfolder, ntasks, cpus, tlim, env, outfolder=None):
"""
Prepare the outfolders and submit a TrufaJob
"""
try:
scripttrufa = TrufaJob( jobname, cmd, dep, jobfolder, ntasks, cpus, tlim, env, outfolder)
scripttrufa.makeOutFolder()
slurm_id=scripttrufa.script()
except Exception as e:
logging.error(e)
sys.exit()
return slurm_id
#-------------------------------------------------------------------------------
def setReadOut( names_in, suffix):
""" To setup the names of the output for the cleaning steps
"""
# Setup the reads files basenames for the cleaning outputs
names_in = names_in.replace("'", "").split(" ")
ext = [ os.path.splitext(x)[-1] for x in names_in ]
basenames = [ os.path.splitext(os.path.basename(x))[0]
for x in names_in ]
names_out = "'" + " ".join( [ x + suffix + y
for x, y in zip(basenames, ext) ] ) + "'"
return names_out
#-------------------------------------------------------------------------------
# MAIN
#-------------------------------------------------------------------------------
logging.getLogger().setLevel( logging.DEBUG )
configLog()
logging.info("Start server side")
# INIT VAR: # Not in the same line because of issues with values assignments
slurm_ids = []
dep = []
blat_dep = []
hmmer_dep = []
b2go_dep = []
expr_dep = []
COMMAND_MODE = checkIfCommandLine()
REALUSER, job_num, para_dict, DEBUG = setUidJid(COMMAND_MODE)
folders_dict, COMMAND_PATH, BLAST_DB_FOLDER, HMMER_PROFILE_FOLDER = setPaths()
makeOutputFolders(folders_dict)
input_dict, READS_FILES, READS_FILES_COUNT, BLATN_CUSTOM_READS,BLATN_CUSTOM_ASS, BLATX_CUSTOM_ASS, HMMER_CUSTOM_DB = getInput(para_dict)
steps = input_dict["progs"]
env = setBashEnv(input_dict, folders_dict)
# Make LOG for debugging
sj.make_log(REALUSER, input_dict, folders_dict["OUT_FOLDER"] + ".tmp1.txt")
# Check and file decompression
new_READS_FILES, files_to_unzip = checkIfCompressedReads(folders_dict, READS_FILES)
if files_to_unzip and not DEBUG:
dep = extract(files_to_unzip, folders_dict["OUT_FOLDER"], COMMAND_PATH, dep)
# Resetting READS_FILES variable to point to extracted files
env["READS_FILES"] = "'" + " ".join(new_READS_FILES) + "'"
#-------------------------------------------------------------------------------
if "FASTQC1" in steps:
#Generate the docker job
prepareScript("fastqc",
"cleaning/larafastqc.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT,2,"03:00:00",env,
folders_dict["STAT_FOLDER"] + "fastqc_report")
slurm_id = prepareAndSubmit("fastqc",
"dockers/cleaning/fastqc.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT,2,"03:00:00",env,
folders_dict["STAT_FOLDER"] + "fastqc_report")
slurm_ids.append( slurm_id )
# Fastqc doesn't have to be incorporated in the dependency list
#-------------------------------------------------------------------------------
# If any program of the cleaning step is on:
if soft_data.cleaning_progs & steps:
os.mkdir(folders_dict["CLEANING_FOLDER"])
#-------------------------------------------------------------------------------
if "CUTADAPT" in steps:
env["READS_OUT"] = setReadOut( env["READS_FILES"], "_noad" )
prepareScript("cutadapt",
"cleaning/laracutadapt.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT,16,"06:00:00", env)
slurm_id = prepareAndSubmit("cutadapt",
"dockers/cleaning/cutadapt.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT,16,"06:00:00", env)
slurm_ids.append(slurm_id)
dep.append(slurm_id)
# Set input for next step:
env["READS_FILES"] = env["READS_OUT"]
#-------------------------------------------------------------------------------
if "DUP" in steps:
env["READS_OUT"] = setReadOut( env["READS_FILES"], "_nodup" )
prepareScript("dup_prinseq",
"cleaning/laraprinseq_dup.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 16, "24:00:00", env)
slurm_id = prepareAndSubmit("dup_prinseq",
"dockers/cleaning/prinseq_dup.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 16, "24:00:00", env)
slurm_ids.append(slurm_id)
dep.append(slurm_id)
# Set input for next step:
env["READS_FILES"] = env["READS_OUT"]
#-------------------------------------------------------------------------------
if "TRIM" in steps:
env["READS_OUT"] = setReadOut( env["READS_FILES"], "_trim" )
prepareScript("trim_prinseq",
"cleaning/laraprinseq_trim.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT, 16, "72:00:00", env)
slurm_id = prepareAndSubmit("trim_prinseq",
"dockers/cleaning/prinseq_trim.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT, 16, "72:00:00", env)
slurm_ids.append(slurm_id)
dep.append(slurm_id)
# Set input for next step:
env["READS_FILES"] = env["READS_OUT"]
#-------------------------------------------------------------------------------
# if there is any BLAT for the reads:
if soft_data.blat_reads_progs & steps:
env["READS_OUT"] = setReadOut( env["READS_FILES"], "_blat" )
# Convert to fasta:
prepareScript("fq2fas",
"cleaning/larafq2fas.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT, 4, "1:00:00", env)
slurm_id = prepareAndSubmit("fq2fas",
"dockers/cleaning/fq2fas.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT, 4, "1:00:00", env)
slurm_ids.append(slurm_id)
dep.append(slurm_id)
# Split for faster BLAT:
prepareScript("split4rblat",
"cleaning/larasplitting.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT, 4, "1:00:00", env)
slurm_id = prepareAndSubmit("split4rblat",
"dockers/cleaning/splitting.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT, 4, "1:00:00", env)
slurm_ids.append(slurm_id)
dep.append(slurm_id)
#-------------------------------------------------------------------------------
if "BLAT_UNIVEC" in steps:
env["BLAT_READS_DB"] = BLAST_DB_FOLDER + "univec/univec"
env["BLAT_TYPE"] = "'-t=dna -q=dna'"
prepareScript("rblat_univec",
"cleaning/larablat.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT * 32, 1, "6:00:00", env)
slurm_id = prepareAndSubmit("rblat_univec",
"dockers/cleaning/blat.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT * 32, 1, "6:00:00", env)
slurm_ids.append(slurm_id)
blat_dep.append(slurm_id)
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
if "BLAT_ECOLI" in steps:
env["BLAT_READS_DB"] = BLAST_DB_FOLDER + "E_coli_G/E_coli_G"
env["BLAT_TYPE"] = "'-t=dna -q=dna'"
prepareScript("rblat_ecoli",
"cleaning/larablat.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT * 32, 1, "6:00:00", env)
slurm_id = prepareAndSubmit("rblat_ecoli",
"dockers/cleaning/blat.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT * 32, 1, "6:00:00", env)
slurm_ids.append(slurm_id)
blat_dep.append(slurm_id)
#-------------------------------------------------------------------------------
if "BLAT_SCERE" in steps:
env["BLAT_READS_DB"] = BLAST_DB_FOLDER + "S_cerevisiae_G/S_cerevisiae_G"
env["BLAT_TYPE"] = "'-t=dna -q=dna'"
prepareScript("rblat_scere",
"cleaning/larablat.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT * 32, 1, "6:00:00", env)
slurm_id = prepareAndSubmit("rblat_scere",
"dockers/cleaning/blat.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT * 32, 1, "6:00:00", env)
slurm_ids.append(slurm_id)
#------------------------------------------------------------------------------
if "BLAT_CUSTOM_READS" in steps:
for db in BLATN_CUSTOM_READS:
env["BLAT_READS_DB"] = DATA_FOLDER + db
env["BLAT_TYPE"] = "'-t=dna -q=dna'"
prepareScript("rblat_" + db,
"cleaning/larablat.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT * 32, 1, "6:00:00", env)
slurm_id = prepareAndSubmit("rblat_" + db,
"dockers/cleaning/blat.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT * 32, 1, "6:00:00", env)
slurm_ids.append(slurm_id)
blat_dep.append(slurm_id)
#-------------------------------------------------------------------------------
# CLEANING FROM BLAT HITS:
prepareScript("blat_parser",
"cleaning/larablat_parser.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
1, 16, "2:00:00", env)
slurm_id = prepareAndSubmit("blat_parser",
"dockers/cleaning/blat_parser.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
1, 16, "2:00:00", env)
slurm_ids.append(slurm_id)
dep.append(slurm_id)
slurm_id = prepareAndSubmit("reads_removal",
"cleaning/reads_removal.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 1, "3:00:00", env)
slurm_ids.append(slurm_id)
dep.append(slurm_id)
# Set input for next step:
env["READS_FILES"] = env["READS_OUT"]
#-------------------------------------------------------------------------------
# Pointing to clean reads files
# If a cleaning has been first performed have to add the CLEANING_FOLDER PATH
if soft_data.cleaning_progs & steps:
reads_tmp = env["READS_FILES"].replace("'", "").split()
env["READS_FILES"] = "'" + " ".join([ folders_dict["CLEANING_FOLDER"] + x
for x in reads_tmp ]) + "'"
print( "'" + " ".join([ folders_dict["CLEANING_FOLDER"] + x
for x in reads_tmp ]) + "'")
#-------------------------------------------------------------------------------
if "FASTQC2" in steps:
prepareScript("fastqc2",
"cleaning/larafastqc2.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT, 2, "03:00:00", env,
folders_dict["STAT_FOLDER"] + "fastqc2_report")
slurm_id = prepareAndSubmit("fastqc2",
"dockers/cleaning/fastqc2.cmd",
dep,
folders_dict["OUT_FOLDER"],
READS_FILES_COUNT, 2, "03:00:00", env,
folders_dict["STAT_FOLDER"] + "fastqc2_report")
slurm_ids.append( slurm_id )
# Fastqc doesn't have to be incorporated in the dependency list
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
# ASSEMBLY
#-------------------------------------------------------------------------------
if soft_data.ass_map_progs & steps:
os.mkdir(folders_dict["ASSEMBLY_MAPPING_FOLDER"])
#-------------------------------------------------------------------------------
if "TRINITY" in steps:
prepareScript("trinity",
"ass_map/laratrinity.cmd",
dep,
folders_dict["OUT_FOLDER"],
2, 16, "72:00:00", env)
slurm_id = prepareAndSubmit("trinity",
"dockers/ass_map/trinity.cmd",
dep,
folders_dict["OUT_FOLDER"],
2, 16, "72:00:00", env)
slurm_ids.append( slurm_id )
dep.append(slurm_id)
# Setting the ASSEMBLY_FILE variable
env["ASSEMBLY_FILE"] = folders_dict["ASSEMBLY_MAPPING_FOLDER"] + "trinity/Trinity.fasta"
#-------------------------------------------------------------------------------
if "CDHITEST" in steps:
prepareScript("cdhitest",
"ass_map/laraclustering.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 16, "72:00:00", env)
slurm_id = prepareAndSubmit("cdhitest",
"dockers/ass_map/clustering.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 16, "72:00:00", env)
slurm_ids.append( slurm_id )
dep.append(slurm_id)
env["ASSEMBLY_FILE"]= folders_dict["ASSEMBLY_MAPPING_FOLDER"] + "cdhitest/assembly_clust.fas"
#-------------------------------------------------------------------------------
if "ASSEMBLY_QUAL" in steps:
env["BLAST_QUAL_DB"] = BLAST_DB_FOLDER + "uniprot_qc/uniprot_sprot.fasta"
prepareScript("qc_blast",
"ass_map/larablast_qc.cmd", dep,
folders_dict["OUT_FOLDER"], 1, 16,
"24:00:00", env,
folders_dict["STAT_FOLDER"] +
"assembly_qc/blast_qc")
slurm_id = prepareAndSubmit("qc_blast",
"dockers/ass_map/blast_qc.cmd", dep,
folders_dict["OUT_FOLDER"], 1, 16,
"24:00:00", env,
folders_dict["STAT_FOLDER"] +
"assembly_qc/blast_qc")
slurm_ids.append( slurm_id )
prepareScript("cegma",
"ass_map/laracegma.cmd", dep,
folders_dict["OUT_FOLDER"], 1, 16,
"24:00:00", env,
folders_dict["STAT_FOLDER"] +
"assembly_qc/cegma")
slurm_id = prepareAndSubmit("cegma",
"dockers/ass_map/cegma.cmd", dep,
folders_dict["OUT_FOLDER"], 1, 16,
"24:00:00", env,
folders_dict["STAT_FOLDER"] +
"assembly_qc/cegma")
slurm_ids.append( slurm_id )
#-------------------------------------------------------------------------------
if "BOWTIE1" in steps:
prepareScript("bowtie1",
"ass_map/larabowtie.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 16, "72:00:00", env)
slurm_id = prepareAndSubmit("bowtie1",
"dockers/ass_map/bowtie.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 16, "72:00:00", env)
slurm_ids.append( slurm_id )
# TO CHANGE WHEN EXPRESSION INCORPORATED:
# bowtie isn't in dependency list yet
#-------------------------------------------------------------------------------
if "BOWTIE2" in steps:
prepareScript("bowtie2",
"ass_map/larabowtie2.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 16, "24:00:00", env)
slurm_id = prepareAndSubmit("bowtie2",
"dockers/ass_map/bowtie2.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 16, "24:00:00", env)
slurm_ids.append( slurm_id )
expr_dep.append(slurm_id)
# Bam postprocessing
prepareScript("bam_postprocess",
"ass_map/larabam_postproc.cmd",
expr_dep,
folders_dict["OUT_FOLDER"],
1, 16, "24:00:00", env)
slurm_id = prepareAndSubmit("bam_postprocess",
"dockers/ass_map/bam_postproc.cmd",
expr_dep,
folders_dict["OUT_FOLDER"],
1, 16, "24:00:00", env)
slurm_ids.append( slurm_id )
expr_dep.append(slurm_id)
#-------------------------------------------------------------------------------
# IDENTIFICATION / ANNOTATION
#-------------------------------------------------------------------------------
print steps
if soft_data.identify_progs & steps:
# OUTPUT folder:
os.mkdir(folders_dict["IDENTIFICATION_FOLDER"])
# If at least one blat search:
if soft_data.blat_ass_progs & steps:
#splitting assembly file:
prepareScript("split4cblat",
"identify/larasplitting.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 4, "00:30:00", env)
slurm_id = prepareAndSubmit("split4cblat",
"dockers/identify/splitting.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 4, "00:30:00", env)
slurm_ids.append( slurm_id )
blat_dep.append(slurm_id)
#-------------------------------------------------------------------------------
if "BLAT_CEGMA" in steps:
env["BLAT_CONTIGS_DB"] = BLAST_DB_FOLDER + "cegma_euk_prot_core/cegma_euk_prot_core"
env["BLAT_TYPE"] = "'-t=dnax -q=prot'"
prepareScript("cblat_cegma",
"identify/larablat.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
64, 1, "72:00:00", env)
slurm_id = prepareAndSubmit("cblat_cegma",
"dockers/identify/blat.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
64, 1, "72:00:00", env)
slurm_ids.append( slurm_id )
blat_dep.append(slurm_id)
#-------------------------------------------------------------------------------
if "BLAT_UNIREF" in steps:
env["BLAT_CONTIGS_DB"] = BLAST_DB_FOLDER + "uniref90/uniref90"
env["BLAT_TYPE"] = "'-t=dnax -q=prot'"
prepareScript("cblat_uniref",
"identify/larablat.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
64, 1, "72:00:00", env)
slurm_id = prepareAndSubmit("cblat_uniref",
"dockers/identify/blat.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
64, 1, "72:00:00", env)
slurm_ids.append( slurm_id )
blat_dep.append(slurm_id)
#-------------------------------------------------------------------------------
if "BLAT_NR" in steps:
env["BLAT_CONTIGS_DB"] = BLAST_DB_FOLDER + "nr/nr"
env["BLAT_TYPE"] = "'-t=dnax -q=prot'"
prepareScript("cblat_nr",
"identify/larablat.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
64, 1, "72:00:00", env)
slurm_id = prepareAndSubmit("cblat_nr",
"dockers/identify/blat.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
64, 1, "72:00:00", env)
slurm_ids.append( slurm_id )
blat_dep.append(slurm_id)
#-------------------------------------------------------------------------------
if "BLAT_CUSTOM_ASS" in steps:
for db in BLATN_CUSTOM_ASS:
env["BLAT_CONTIGS_DB"] = folders_dict["DATA_FOLDER"] + db
env["BLAT_TYPE"] = "'-t=dna -q=dna'"
prepareScript("cblatn_"+db,
"identify/larablat.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
64, 1, "72:00:00", env)
slurm_id = prepareAndSubmit("cblatn_"+db,
"dockers/identify/blat.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
64, 1, "72:00:00", env)
slurm_ids.append( slurm_id )
blat_dep.append(slurm_id)
for db in BLATX_CUSTOM_ASS:
env["BLAT_CONTIGS_DB"] = folders_dict["DATA_FOLDER"] + db
env["BLAT_TYPE"] = "'-t=dnax -q=prot'"
prepareScript("cblatx_"+db,
"identify/larablat.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
64, 1, "72:00:00", env)
slurm_id = prepareAndSubmit("cblatx_"+db,
"dockers/identify/blat.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
64, 1, "72:00:00", env)
slurm_ids.append( slurm_id )
blat_dep.append(slurm_id)
# Tidying blat outputs
prepareScript("cleaning_blat",
"identify/laraafter_blat_cleaning.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
1, 1, "00:30:00", env)
slurm_id = prepareAndSubmit("cleaning_blat",
"dockers/identify/after_blat_cleaning.cmd",
blat_dep,
folders_dict["OUT_FOLDER"],
1, 1, "00:30:00", env)
slurm_ids.append( slurm_id )
blat_dep.append(slurm_id)
#-------------------------------------------------------------------------------
# If at least one HMMER search:
if soft_data.hmmer_ass_progs & steps:
prepareScript("split4hmmer",
"identify/larasplitting_4_hmmer.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 4, "01:00:00", env)
slurm_id= prepareAndSubmit("split4hmmer",
"dockers/identify/splitting_4_hmmer.cmd",
dep,
folders_dict["OUT_FOLDER"],
1, 4, "01:00:00", env)
slurm_ids.append( slurm_id )
hmmer_dep.append(slurm_id)
#-------------------------------------------------------------------------------
if "HMMER_PFAMA" in steps:
env["HMM_PROFILE"] = "PfamA"
env["HMM_PATH"] = HMMER_PROFILE_FOLDER
prepareScript("hmm_scan",
"identify/larahmmer_scan.cmd",
hmmer_dep,
folders_dict["OUT_FOLDER"],
6, 16, "72:00:00", env)
slurm_id = prepareAndSubmit("hmm_scan",
"dockers/identify/hmmer_scan.cmd",
hmmer_dep,
folders_dict["OUT_FOLDER"],
6, 16, "72:00:00", env)
slurm_ids.append( slurm_id )
hmmer_dep.append(slurm_id)
#-------------------------------------------------------------------------------
if "HMMER_PFAMB" in steps:
env["HMM_PROFILE"] = "PfamB"
env["HMM_PATH"] = HMMER_PROFILE_FOLDER
prepareScript("hmm_scan",
"identify/larahmmer_scan.cmd",
hmmer_dep,
folders_dict["OUT_FOLDER"],
6, 16, "72:00:00", env)
slurm_id = prepareAndSubmit("hmm_scan",
"dockers/identify/hmmer_scan.cmd",
hmmer_dep,
folders_dict["OUT_FOLDER"],
6, 16, "72:00:00", env)
slurm_ids.append( slurm_id )
hmmer_dep.append(slurm_id)
#-------------------------------------------------------------------------------
if "HMMER_CUSTOM" in steps:
for db in HMMER_CUSTOM_DB:
env["HMM_PROFILE"] = os.path.basename(db)
env["HMM_PATH"] = folders_dict["DATA_FOLDER"] + db
prepareScript("hmm_scan",
"identify/larahmmer_scan_custom.cmd",
hmmer_dep,
folders_dict["OUT_FOLDER"],
6, 16, "72:00:00", env)
slurm_id = prepareAndSubmit("hmm_scan",
"dockers/identify/hmmer_scan_custom.cmd",
hmmer_dep,
folders_dict["OUT_FOLDER"],
6, 16, "72:00:00", env)
slurm_ids.append( slurm_id )
hmmer_dep.append(slurm_id)
# Tidying hmmer outputs
prepareScript("cleaning_hmmer",
"identify/laraafter_hmmer_cleaning.cmd",
hmmer_dep,
folders_dict["OUT_FOLDER"],
1, 1, "00:30:00", env)
slurm_id = prepareAndSubmit("cleaning_hmmer",
"dockers/identify/after_hmmer_cleaning.cmd",
hmmer_dep,
folders_dict["OUT_FOLDER"],
1, 1, "00:30:00", env)
slurm_ids.append( slurm_id )
hmmer_dep.append(slurm_id)
#-------------------------------------------------------------------------------
if "BLASTPLUS_NR" in steps:
prepareScript("blastplus_nr",
"identify/larablastplus_par.cmd",
dep,
folders_dict["OUT_FOLDER"],
16, 16, "72:00:00", env,
folders_dict["IDENTIFICATION_FOLDER"] +
"blastplus_par")
slurm_id = prepareAndSubmit("blastplus_nr",
"dockers/identify/blastplus_par.cmd",
dep,
folders_dict["OUT_FOLDER"],
16, 16, "72:00:00", env,
folders_dict["IDENTIFICATION_FOLDER"] +
"blastplus_par")
slurm_ids.append( slurm_id )
b2go_dep.append(slurm_id)
prepareScript("merge_xml",
"identify/laramerge_xml.cmd",
b2go_dep,
folders_dict["OUT_FOLDER"],
1, 8, "01:00:00", env)
slurm_id = prepareAndSubmit("merge_xml",
"dockers/identify/merge_xml.cmd",
b2go_dep,
folders_dict["OUT_FOLDER"],
1, 8, "01:00:00", env)
slurm_ids.append( slurm_id )
b2go_dep.append(slurm_id)
#-------------------------------------------------------------------------------
if "INTERPROSCAN" in steps:
prepareScript("ipscan",
"identify/laraipscan.cmd",
dep,
folders_dict["OUT_FOLDER"],
64, 1, "72:00:00", env)
slurm_id = prepareAndSubmit("ipscan",
"dockers/identify/ipscan.cmd",
dep,
folders_dict["OUT_FOLDER"],
64, 1, "72:00:00", env)
slurm_ids.append( slurm_id )
b2go_dep.append(slurm_id)
#-------------------------------------------------------------------------------
if "BLAST2GO" in steps:
if "BLASTPLUS_NR" in steps:
prepareScript("b2go_blastplus",
"identify/larab2go_blastplus.cmd",
b2go_dep,
folders_dict["OUT_FOLDER"],