def sortIndexBAMs(self, path_to_exe=False, force=False, max_cpus=-1):
if not path_to_exe:
path_to_exe = _get_exe_path('samtools')
processes = set()
max_processes = _decide_max_processes(max_cpus)
paths_to_BAMs_dd_si = []
for SAM in self.paths_to_BAMs_dd:
BAM_out = SAM[:-4] + '_si.bam'
if not _os.path.exists(BAM_out) or force:
cmd = '{0} sort {1} {2}_si; {0} index {2}_si.bam'.format(
path_to_exe, SAM, SAM[:-4])
print('Called: %s' % cmd)
processes.add(_subprocess.Popen(cmd, shell=True))
if len(processes) >= max_processes:
(pid, exit_status) = _os.wait()
processes.difference_update(
[p for p in processes if p.poll() is not None])
else:
print('Found:')
print(BAM_out)
print('use "force = True" to overwrite')
paths_to_BAMs_dd_si += [BAM_out]
# Check if all the child processes were closed
for p in processes:
if p.poll() is None:
p.wait()
self.paths_to_BAMs_dd_si = paths_to_BAMs_dd_si
def sortIndexBAMs(self, path_to_exe = False, force = False, max_cpus = -1):
if not path_to_exe:
path_to_exe = _get_exe_path('samtools')
processes = set()
max_processes = _decide_max_processes( max_cpus )
paths_to_BAMs_dd_si = []
for SAM in self.paths_to_BAMs_dd:
BAM_out = SAM[:-4] + '_si.bam'
if not _os.path.exists(BAM_out) or force:
cmd = '{0} sort {1} {2}_si; {0} index {2}_si.bam'.format(path_to_exe, SAM, SAM[:-4])
print('Called: %s' % cmd)
processes.add( _subprocess.Popen(cmd, shell=True) )
if len(processes) >= max_processes:
(pid, exit_status) = _os.wait()
processes.difference_update(
[p for p in processes if p.poll() is not None])
else:
print('Found:')
print(BAM_out)
print('use "force = True" to overwrite')
paths_to_BAMs_dd_si += [BAM_out]
# Check if all the child processes were closed
for p in processes:
if p.poll() is None:
p.wait()
self.paths_to_BAMs_dd_si = paths_to_BAMs_dd_si
def SPAdes(self,
exe=[],
output_folder=['assemblies', 'SPAdes'],
mem_num_gigs=8,
max_cpus=-1,
single_assembly=False,
careful=True,
only_assembler=False):
'''
de novo assembly of short reads using SPAdes
By default, the provided short reads in dictionary: self.paths_to_reads
will be assembled separately, unless single_assembly set to True in
which case each set of paired read fastq files will be used in a
single assembly.
http://spades.bioinf.spbau.ru/release3.6.1/manual.html
relevent inputs:
-o <output_dir> Specify the output directory. Required option.
--sc required for MDA (single-cell) data.
--only-error-correction
--only-assembler
--careful reduce the number of mismatches and short indels. Run MismatchCorrector – a post processing tool. Recommended.
--continue from the specified output folder starting from the last available check-point
--restart-from <check_point>
ec start from error correction
as restart assembly module from the first iteration
k<int> restart from the iteration with specified k values, e.g. k55
mc restart mismatch correction
--pe1-12 <file_name> interlaced forward and reverse paired-end reads.
--pe1-1 <file_name> File with forward reads.
--pe1-2 <file_name> File with reverse reads.
--pe1-s <file_name> File with unpaired reads . . use --pe2-... for next library
--threads <int>
--memory <int> max memory in Gb
-k <int,int,...> Comma-separated list of odd ascending k-mers
If --sc is set the default value are 21,33,55, for multicell data sets it is auto
--cov-cutoff <float> positive float value, or 'auto', or 'off'. Default value is 'off'
'''
assert isinstance(
output_folder,
list), 'Provide output folder as list of folders forming path'
base_output_path = _os.path.sep.join(output_folder)
if not _os.path.exists(base_output_path):
_os.makedirs(base_output_path)
# max threads is slightly different to cpus
# . . can probably use more
max_processes = _decide_max_processes(max_cpus)
# if an exe is not provided, use that stored in Dependencies
if len(exe):
use_exe = _os.path.sep.join(exe)
else:
from baga import Dependencies
use_exe = _get_exe_path('spades')
def run_SPAdes(cmd):
proc = _subprocess.Popen(cmd,
stdout=_subprocess.PIPE,
stderr=_subprocess.PIPE)
# allow for failed SPAdes runs (possibly caused by small fastq files) <== but also check they were actually built properly
try:
stdout_value, stderr_value = proc.communicate()
checkthese = []
getline = False
for line in stdout_value.split('\n'):
if 'Warnings saved to' in line:
getline = False
if getline:
l = line.rstrip()
if len(l):
checkthese += [l]
if 'SPAdes pipeline finished WITH WARNINGS!' in line:
getline = True
if len(checkthese):
print('SPAdes completed with warnings:\n{}\n'.format(
'\n'.join(checkthese)))
else:
print('SPAdes completed without warnings')
# with open('___SPAdes_{}_good_{}.log'.format(cnum, thetime), 'w') as fout:
# fout.write(stdout_value)
path2contigs = _os.path.sep.join(
[this_output_path, 'contigs.fasta'])
except _subprocess.CalledProcessError as e:
print('SPAdes probably did not complete: error returned ({})'.
format(proc.returncode))
print('Error: {}'.format(e))
print(
'Writing some info relevent to SPAdes crash to ___SPAdes_{}_bad_{}.log'
.format(cnum, thetime))
with open('___SPAdes_{}_bad_{}.log'.format(cnum, thetime),
'w') as fout:
fout.write(dir(proc))
fout.write('\n' + str(e.returncode) + '\n')
fout.write(
_os.path.sep.join([this_output_path, 'contigs.fasta']))
path2contigs = None
return (path2contigs)
if isinstance(use_exe, list):
# allow for use of prepended executable with script to run
cmd = list(use_exe)
else:
# or just executable
cmd = [use_exe]
contigs = {}
if single_assembly:
print(
'Combining reads aligned at multiple regions into single assembly'
)
if isinstance(use_exe, list):
# allow for use of prepended executable with script to run
cmd = list(use_exe)
else:
# or just executable
cmd = [use_exe]
for cnum, (pairname, files) in enumerate(self.read_files.items()):
# allow use of tuples or dicts by converting dicts to lists
if isinstance(files, dict):
use_files = []
for k, v in sorted(files.items()):
use_files += [v]
else:
use_files = files
cmd += ['--pe{}-1'.format(cnum + 1), use_files[0]]
cmd += ['--pe{}-2'.format(cnum + 1), use_files[1]]
try:
# use unpaired reads if available
cmd += ['--pe{}-s'.format(cnum + 1), use_files[2]]
except IndexError:
pass
try:
# add a second library if provided
if isinstance(self.read_files2[pairname], dict):
# if a dict supplied, make it a list
use_files2 = []
for k, v in sorted(self.read_files2[pairname].items()):
use_files2 += [v]
else:
use_files2 = self.read_files2[pairname]
cmd += ['--pe{}-1'.format(cnum + 2), use_files2[0]]
cmd += ['--pe{}-2'.format(cnum + 2), use_files2[1]]
try:
cmd += ['--pe{}-s'.format(cnum + 2), use_files2[2]]
except IndexError:
pass
except AttributeError:
pass
## this isn't very flexible:
# retain <sample>__<genome> from pairname:
# pairname == <sample>__<genome>_<start>-<end>+<padding>
# and replace with multiregion
folder = '{}__{}_{}'.format(
pairname.split('__')[0],
pairname.split('__')[1].split('_')[0], 'multi_region')
this_output_path = _os.path.sep.join(output_folder + [folder])
if not _os.path.exists(this_output_path):
_os.makedirs(this_output_path)
cmd += ['-o', this_output_path]
cmd += ['--threads', str(max_processes)]
cmd += ['--memory', str(mem_num_gigs)]
if only_assembler:
cmd += ['--only-assembler']
if careful:
cmd += ['--careful']
thetime = _time.asctime(_time.localtime(_time.time()))
print('about to launch SPAdes . . . at {}'.format(thetime))
print(' '.join(cmd))
contigs['multi_region'] = run_SPAdes(cmd)
else:
start_time = _time.time()
# prepare commandline and launch each SPAdes assembly
contigs = {}
for cnum, (pairname,
files) in enumerate(sorted(self.read_files.items())):
if isinstance(use_exe, list):
# allow for use of prepended executable with script to run
cmd = list(use_exe)
else:
# or just executable
cmd = [use_exe]
# allow use of tuples or dicts by converting dicts to lists
if isinstance(files, dict):
use_files = []
for k, v in sorted(files.items()):
use_files += [v]
else:
use_files = files
cmd += ['--pe1-1', use_files[0]]
cmd += ['--pe1-2', use_files[1]]
try:
# use unpaired reads if available
cmd += ['--pe1-s', use_files[2]]
except IndexError:
pass
try:
# add a second library if provided
if isinstance(self.read_files2[pairname], dict):
# if a dict supplied, make it a list
use_files2 = []
for k, v in sorted(self.read_files2[pairname].items()):
use_files2 += [v]
else:
use_files2 = self.read_files2[pairname]
cmd += ['--pe2-1', use_files2[0]]
cmd += ['--pe2-2', use_files2[1]]
try:
cmd += ['--pe2-s', use_files2[2]]
except IndexError:
pass
except AttributeError:
pass
this_output_path = _os.path.sep.join(output_folder +
[pairname])
if not _os.path.exists(this_output_path):
_os.makedirs(this_output_path)
cmd += ['-o', this_output_path]
cmd += ['--threads', str(max_processes)]
cmd += ['--memory', str(mem_num_gigs)]
if only_assembler:
cmd += ['--only-assembler']
if careful:
cmd += ['--careful']
thetime = _time.asctime(_time.localtime(_time.time()))
print('about to launch SPAdes . . . at {}'.format(thetime))
print(' '.join(cmd))
contigs[pairname] = run_SPAdes(cmd)
if len(self.read_files) > 1:
# report durations, time left etc
_report_time(start_time, cnum, len(self.read_files))
self.paths_to_contigs = contigs
def trim(self, path_to_exe = False,
force = False,
max_cpus = -1):
if not path_to_exe:
exe_sickle = _get_exe_path('sickle')
else:
exe_sickle = _os.path.sep.join(path_to_exe)
e1 = 'Could not find "adaptorcut_read_files" attribute. \
Before quality score trimming, reads must be cleaned of \
library preparation sequences. Please run cutAdaptors() \
method on this Reads instance.'
assert hasattr(self, 'adaptorcut_read_files'), e1
e2 = 'Could not find %s. Either run cutAdaptors() again \
or ensure file exists'
for pairname, files in self.adaptorcut_read_files.items():
assert _os.path.exists(files[1]), e2 % files[1]
assert _os.path.exists(files[1]), e2 % files[1]
trimmed_read_files = {}
print(sorted(self.adaptorcut_read_files))
cmds = []
processed_paths_to_do = []
for pairname,files in self.adaptorcut_read_files.items():
processed_path_1 = insert_suffix(files[1], '_qual')
processed_path_2 = insert_suffix(files[2], '_qual')
processed_path_s = insert_suffix(files[2], '_singletons_qual')
# Illumina quality using CASAVA >= 1.8 is Sanger encoded
QSscore_scale = 'sanger'
cmd = [exe_sickle, 'pe',
'-f', files[1] ,'-r', files[2],
'-t', QSscore_scale,
'-o', processed_path_1,
'-p', processed_path_2,
'-s', processed_path_s,
# quality 25, length 50 (of 150)
'-q','25','-l','50']
if not all([_os.path.exists(processed_path_1),
_os.path.exists(processed_path_2),
_os.path.exists(processed_path_s)]) \
or force:
# collect expected outputs
processed_paths_to_do += [(processed_path_1,processed_path_2,processed_path_s)]
# collect all the commands to be issued
cmds += [(pairname,cmd)]
else:
print('Found:')
print(processed_path_1)
print(processed_path_2)
print(processed_path_s)
print('use "force = True" to overwrite')
trimmed_read_files[pairname] = {}
trimmed_read_files[pairname][1] = processed_path_1
trimmed_read_files[pairname][2] = processed_path_2
if len(cmds):
max_processes = _decide_max_processes(max_cpus)
processes = {}
### how to combine this which hangs on _os.wait()
for pairname,cmd in cmds:
print('Called: "%s"' % ' '.join(cmd))
# process is key, open file being piped to is value
# baga CollectReads currently includes path in pairname
this_stdout_file = open(pairname+'_sickle.log',"w")
thisprocess = _subprocess.Popen(cmd, shell = False, stdout = this_stdout_file)
processes[thisprocess] = this_stdout_file
if len(processes) >= max_processes:
_os.wait()
finished = dict([(p,f) for p,f in processes.items() if p.poll() is not None])
# close files for finished processes
for process,stdout_file in finished.items():
stdout_file.close()
# update active processes
del processes[process]
# Check if all the child processes were closed
for p in processes:
if p.poll() is None:
p.wait()
fails = []
for (pairname,cmd),(processed_path_1,processed_path_2,processed_path_s) in zip(cmds,processed_paths_to_do):
if _os.path.exists(processed_path_1) and _os.path.exists(processed_path_2):
print('Found:')
print(processed_path_1)
print(processed_path_2)
trimmed_read_files[pairname] = {}
trimmed_read_files[pairname][1] = processed_path_1
trimmed_read_files[pairname][2] = processed_path_2
else:
print('Processing of the following pair seems to have failed')
print(processed_path_1)
print(processed_path_2)
fails += [(processed_path_1,processed_path_2)]
assert len(fails) == 0, 'There was a problem finding all of the output from sickle. Try repeating this or an earlier step with the --force option to overwite previous, possibly incomplete, files'
self.trimmed_read_files = trimmed_read_files
def cutAdaptors(self, path_to_exe = False, force = False, max_cpus = -1):
if not path_to_exe:
path_to_exe = _get_exe_path('cutadapt')
adaptorcut_read_files = {}
adaptor_seqs = [
'AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC',
'AGATCGGAAGAGCACACGTCT',
'AGATCGGAAGAGC',
'GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG',
'ACACTCTTTCCCTACACGACGCTCTTCCGATCT',
]
cmds = []
processed_paths_to_do = []
for cnum,(pairname,files) in enumerate(self.read_files.items()):
processed_path_1 = insert_suffix(files[1], '_adpt')
processed_path_2 = insert_suffix(files[2], '_adpt')
# print(files[1], processed_path_1)
# print(files[2], processed_path_2)
# single end
cmd = [path_to_exe] + \
[a for b in [('-a', a) for a in adaptor_seqs] for a in b] + \
['-o', processed_path_1, files[1]]
# paired end
cmd = [path_to_exe] + \
[a for b in [('-a', a) for a in adaptor_seqs] for a in b] + \
[a for b in [('-A', a) for a in adaptor_seqs] for a in b] + \
['-o', processed_path_1, '-p', processed_path_2] + \
[files[1], files[2]]
if not all([_os.path.exists(processed_path_1),
_os.path.exists(processed_path_2)]) \
or force:
# collect expected outputs
processed_paths_to_do += [(processed_path_1,processed_path_2)]
# collect all the commands to be issued
cmds += [(pairname,cmd)]
else:
print('Found:')
print(processed_path_1)
print(processed_path_2)
print('use "force = True" to overwrite')
adaptorcut_read_files[pairname] = {}
adaptorcut_read_files[pairname][1] = processed_path_1
adaptorcut_read_files[pairname][2] = processed_path_2
if len(cmds):
max_processes = _decide_max_processes(max_cpus)
processes = {}
### how to combine this which hangs on _os.wait()
for pairname,cmd in cmds:
print('Called: "%s"' % ' '.join(cmd))
# process is key, open file being piped to is value
# baga CollectReads currently includes path in pairname
this_stdout_file = open(pairname+'_cutadapt.log',"w")
thisprocess = _subprocess.Popen(cmd, shell=False, stdout = this_stdout_file)
processes[thisprocess] = this_stdout_file
if len(processes) >= max_processes:
_os.wait()
finished = dict([(p,f) for p,f in processes.items() if p.poll() is not None])
# close files for finished processes
for process,stdout_file in finished.items():
stdout_file.close()
# update active processes
del processes[process]
# Check if all the child processes were closed
for p in processes:
if p.poll() is None:
p.wait()
fails = []
for (pairname,cmd),(processed_path_1,processed_path_2) in zip(cmds,processed_paths_to_do):
if _os.path.exists(processed_path_1) and _os.path.exists(processed_path_2):
print('Found:')
print(processed_path_1)
print(processed_path_2)
adaptorcut_read_files[pairname] = {}
adaptorcut_read_files[pairname][1] = processed_path_1
adaptorcut_read_files[pairname][2] = processed_path_2
else:
print('Processing of the following pair seems to have failed')
print(processed_path_1)
print(processed_path_2)
fails += [(processed_path_1,processed_path_2)]
assert len(fails) == 0, 'There was a problem finding all of the output from cutadapt. Try repeating this or an eralier step with the --force option to overwite previous, possibly incomplete, files'
self.adaptorcut_read_files = adaptorcut_read_files
def SPAdes(self,
exe = [],
output_folder = ['assemblies','SPAdes'],
mem_num_gigs = 8,
max_cpus = -1,
single_assembly = False,
careful = True,
only_assembler = False):
'''
de novo assembly of short reads using SPAdes
By default, the provided short reads in dictionary: self.paths_to_reads
will be assembled separately, unless single_assembly set to True in
which case each set of paired read fastq files will be used in a
single assembly.
http://spades.bioinf.spbau.ru/release3.6.1/manual.html
relevent inputs:
-o <output_dir> Specify the output directory. Required option.
--sc required for MDA (single-cell) data.
--only-error-correction
--only-assembler
--careful reduce the number of mismatches and short indels. Run MismatchCorrector – a post processing tool. Recommended.
--continue from the specified output folder starting from the last available check-point
--restart-from <check_point>
ec start from error correction
as restart assembly module from the first iteration
k<int> restart from the iteration with specified k values, e.g. k55
mc restart mismatch correction
--pe1-12 <file_name> interlaced forward and reverse paired-end reads.
--pe1-1 <file_name> File with forward reads.
--pe1-2 <file_name> File with reverse reads.
--pe1-s <file_name> File with unpaired reads . . use --pe2-... for next library
--threads <int>
--memory <int> max memory in Gb
-k <int,int,...> Comma-separated list of odd ascending k-mers
If --sc is set the default value are 21,33,55, for multicell data sets it is auto
--cov-cutoff <float> positive float value, or 'auto', or 'off'. Default value is 'off'
'''
assert isinstance(output_folder, list), 'Provide output folder as list of folders forming path'
base_output_path = _os.path.sep.join(output_folder)
if not _os.path.exists(base_output_path):
_os.makedirs(base_output_path)
# max threads is slightly different to cpus
# . . can probably use more
max_processes = _decide_max_processes( max_cpus )
# if an exe is not provided, use that stored in Dependencies
if len(exe):
use_exe = _os.path.sep.join(exe)
else:
from baga import Dependencies
use_exe = _get_exe_path('spades')
def run_SPAdes(cmd):
proc = _subprocess.Popen(cmd, stdout=_subprocess.PIPE, stderr=_subprocess.PIPE)
# allow for failed SPAdes runs (possibly caused by small fastq files) <== but also check they were actually built properly
try:
stdout_value, stderr_value = proc.communicate()
checkthese = []
getline = False
for line in stdout_value.split('\n'):
if 'Warnings saved to' in line:
getline = False
if getline:
l = line.rstrip()
if len(l):
checkthese += [l]
if 'SPAdes pipeline finished WITH WARNINGS!' in line:
getline = True
if len(checkthese):
print('SPAdes completed with warnings:\n{}\n'.format('\n'.join(checkthese)))
else:
print('SPAdes completed without warnings')
# with open('___SPAdes_{}_good_{}.log'.format(cnum, thetime), 'w') as fout:
# fout.write(stdout_value)
path2contigs = _os.path.sep.join([this_output_path,'contigs.fasta'])
except _subprocess.CalledProcessError as e:
print('SPAdes probably did not complete: error returned ({})'.format(proc.returncode))
print('Error: {}'.format(e))
print('Writing some info relevent to SPAdes crash to ___SPAdes_{}_bad_{}.log'.format(cnum, thetime))
with open('___SPAdes_{}_bad_{}.log'.format(cnum, thetime), 'w') as fout:
fout.write(dir(proc))
fout.write('\n' + str(e.returncode) + '\n')
fout.write(_os.path.sep.join([this_output_path,'contigs.fasta']))
path2contigs = None
return(path2contigs)
if isinstance(use_exe, list):
# allow for use of prepended executable with script to run
cmd = list(use_exe)
else:
# or just executable
cmd = [use_exe]
contigs = {}
if single_assembly:
print('Combining reads aligned at multiple regions into single assembly')
if isinstance(use_exe, list):
# allow for use of prepended executable with script to run
cmd = list(use_exe)
else:
# or just executable
cmd = [use_exe]
for cnum, (pairname, files) in enumerate(self.read_files.items()):
# allow use of tuples or dicts by converting dicts to lists
if isinstance(files, dict):
use_files = []
for k,v in sorted(files.items()):
use_files += [v]
else:
use_files = files
cmd += ['--pe{}-1'.format(cnum+1), use_files[0]]
cmd += ['--pe{}-2'.format(cnum+1), use_files[1]]
try:
# use unpaired reads if available
cmd += ['--pe{}-s'.format(cnum+1), use_files[2]]
except IndexError:
pass
try:
# add a second library if provided
if isinstance(self.read_files2[pairname], dict):
# if a dict supplied, make it a list
use_files2 = []
for k,v in sorted(self.read_files2[pairname].items()):
use_files2 += [v]
else:
use_files2 = self.read_files2[pairname]
cmd += ['--pe{}-1'.format(cnum+2), use_files2[0]]
cmd += ['--pe{}-2'.format(cnum+2), use_files2[1]]
try:
cmd += ['--pe{}-s'.format(cnum+2), use_files2[2]]
except IndexError:
pass
except AttributeError:
pass
## this isn't very flexible:
# retain <sample>__<genome> from pairname:
# pairname == <sample>__<genome>_<start>-<end>+<padding>
# and replace with multiregion
folder = '{}__{}_{}'.format(pairname.split('__')[0],
pairname.split('__')[1].split('_')[0],
'multi_region')
this_output_path = _os.path.sep.join(output_folder + [folder])
if not _os.path.exists(this_output_path):
_os.makedirs(this_output_path)
cmd += ['-o', this_output_path]
cmd += ['--threads', str(max_processes)]
cmd += ['--memory', str(mem_num_gigs)]
if only_assembler:
cmd += ['--only-assembler']
if careful:
cmd += ['--careful']
thetime = _time.asctime( _time.localtime(_time.time()) )
print('about to launch SPAdes . . . at {}'.format(thetime))
print(' '.join(cmd))
contigs['multi_region'] = run_SPAdes(cmd)
else:
start_time = _time.time()
# prepare commandline and launch each SPAdes assembly
contigs = {}
for cnum, (pairname, files) in enumerate(sorted(self.read_files.items())):
if isinstance(use_exe, list):
# allow for use of prepended executable with script to run
cmd = list(use_exe)
else:
# or just executable
cmd = [use_exe]
# allow use of tuples or dicts by converting dicts to lists
if isinstance(files, dict):
use_files = []
for k,v in sorted(files.items()):
use_files += [v]
else:
use_files = files
cmd += ['--pe1-1', use_files[0]]
cmd += ['--pe1-2', use_files[1]]
try:
# use unpaired reads if available
cmd += ['--pe1-s', use_files[2]]
except IndexError:
pass
try:
# add a second library if provided
if isinstance(self.read_files2[pairname], dict):
# if a dict supplied, make it a list
use_files2 = []
for k,v in sorted(self.read_files2[pairname].items()):
use_files2 += [v]
else:
use_files2 = self.read_files2[pairname]
cmd += ['--pe2-1', use_files2[0]]
cmd += ['--pe2-2', use_files2[1]]
try:
cmd += ['--pe2-s', use_files2[2]]
except IndexError:
pass
except AttributeError:
pass
this_output_path = _os.path.sep.join(output_folder + [pairname])
if not _os.path.exists(this_output_path):
_os.makedirs(this_output_path)
cmd += ['-o', this_output_path]
cmd += ['--threads', str(max_processes)]
cmd += ['--memory', str(mem_num_gigs)]
if only_assembler:
cmd += ['--only-assembler']
if careful:
cmd += ['--careful']
thetime = _time.asctime( _time.localtime(_time.time()) )
print('about to launch SPAdes . . . at {}'.format(thetime))
print(' '.join(cmd))
contigs[pairname] = run_SPAdes(cmd)
if len(self.read_files) > 1:
# report durations, time left etc
_report_time(start_time, cnum, len(self.read_files))
self.paths_to_contigs = contigs
def IndelRealignGATK(self,
jar = ['external_programs', 'GenomeAnalysisTK', 'GenomeAnalysisTK.jar'],
picard_jar = False,
samtools_exe = False,
use_java = 'java',
force = False,
mem_num_gigs = 2,
max_cpus = -1):
# GATK is manually downloaded by user and placed in folder of their choice
jar = _os.path.sep.join(jar)
if not picard_jar:
picard_jar = _get_jar_path('picard')
if not samtools_exe:
samtools_exe = _get_exe_path('samtools')
genome_fna = 'genome_sequences/{}.fna'.format(self.genome_id)
e1 = 'Could not find "paths_to_BAMs_dd_si" attribute. Before starting GATK analysis, read alignments must have duplicates removed. Please run: .toBAMS(), .removeDuplicates(), .sortIndexBAMs() methods on this SAMs instance, or --deduplicate if using baga_cli.py.'
assert hasattr(self, 'paths_to_BAMs_dd_si'), e1
e2 = 'Could not find %s. Please ensure file exists'
for BAM in self.paths_to_BAMs_dd_si:
assert _os.path.exists(BAM), e2 % BAM
if not _os.path.exists(genome_fna[:-4] + '.dict'):
print('Creating sequence dictionary for %s' % genome_fna)
_subprocess.call([use_java, '-jar', picard_jar, 'CreateSequenceDictionary', 'R=', genome_fna, 'O=', genome_fna[:-4] + '.dict'])
#have_index_files = [_os.path.exists(genome_fna + '.' + a) for a in ('ann','pac','amb','bwt','sa','fai')]
have_index_files = [_os.path.exists(genome_fna + '.' + a) for a in ('fai',)]
if not all(have_index_files):
print('Writing index files for %s' % genome_fna)
_subprocess.call([samtools_exe, 'faidx', genome_fna])
processes = set()
max_processes = _decide_max_processes( max_cpus )
for BAM in self.paths_to_BAMs_dd_si:
intervals = BAM[:-4] + '.intervals'
if not _os.path.exists(intervals) or force:
cmd = [use_java, '-Xmx%sg' % mem_num_gigs, '-jar', jar,
'-T', 'RealignerTargetCreator',
'-R', genome_fna,
'-I', BAM,
'-o', intervals] #, '--validation_strictness', 'LENIENT']
print(' '.join(map(str, cmd)))
processes.add( _subprocess.Popen(cmd, shell=False) )
if len(processes) >= max_processes:
(pid, exit_status) = _os.wait()
processes.difference_update(
[p for p in processes if p.poll() is not None])
else:
print('Found:')
print(intervals)
print('use "force = True" to overwrite')
# Check if all the child processes were closed
for p in processes:
if p.poll() is None:
p.wait()
paths_to_BAMs_dd_si_ra = []
for BAM in self.paths_to_BAMs_dd_si:
intervals = BAM[:-4] + '.intervals'
bam_out = BAM[:-4] + '_realn.bam'
if not _os.path.exists(bam_out) or force:
cmd = [use_java, '-Xmx4g', '-jar', jar,
'-T', 'IndelRealigner',
'-R', genome_fna,
'-I', BAM,
'-targetIntervals', intervals,
'-o', bam_out,
'--filter_bases_not_stored']
print(' '.join(map(str, cmd)))
processes.add( _subprocess.Popen(cmd, shell=False) )
if len(processes) >= max_processes:
_os.wait()
processes.difference_update(
[p for p in processes if p.poll() is not None])
else:
print('Found:')
print(bam_out)
print('use "force = True" to overwrite')
paths_to_BAMs_dd_si_ra += [bam_out]
for p in processes:
if p.poll() is None:
p.wait()
# the last list of BAMs in ready_BAMs is input for CallgVCFsGATK
# both IndelRealignGATK and recalibBaseScoresGATK put here
self.ready_BAMs = [paths_to_BAMs_dd_si_ra]
def align(self, insert_size = False,
path_to_exe = False,
local_alns_path = ['alignments'],
force = False,
max_cpus = -1):
if not path_to_exe:
path_to_exe = _get_exe_path('bwa')
# write genome sequence to a fasta file
try:
_os.makedirs('genome_sequences')
except OSError:
pass
genome_fna = 'genome_sequences/%s.fna' % self.genome_id
_SeqIO.write(_SeqRecord(_Seq(self.genome_sequence.tostring()), id = self.genome_id),
genome_fna,
'fasta')
# make folder for alignments (BAMs)
local_alns_path = _os.path.sep.join(local_alns_path)
if not _os.path.exists(local_alns_path):
_os.makedirs(local_alns_path)
# make a subdir for this genome
local_alns_path_genome = _os.path.sep.join([
local_alns_path,
self.genome_id])
if not _os.path.exists(local_alns_path_genome):
_os.makedirs(local_alns_path_genome)
max_processes = _decide_max_processes( max_cpus )
e1 = 'Could not find "read_files" attribute. Before aligning to genome, reads must be quality score trimmed. Please run trim() method on this Reads instance.'
assert hasattr(self, 'read_files'), e1
e2 = 'Could not find %s. Either run trim() again or ensure file exists'
for pairname, files in self.read_files.items():
assert _os.path.exists(files[1]), e2 % files[1]
assert _os.path.exists(files[2]), e2 % files[2]
have_index_files = [_os.path.exists(genome_fna + '.' + a) for a in ('ann','pac','amb','bwt','sa')]
if not all(have_index_files):
print('Writing BWA index files for %s' % genome_fna)
_subprocess.call([path_to_exe, 'index', genome_fna])
aligned_read_files = {}
for pairname,files in self.read_files.items():
RGinfo = r"@RG\tID:%s\tSM:%s\tPL:ILLUMINA" % (pairname,pairname)
if insert_size:
cmd = [path_to_exe, 'mem', '-t', str(max_processes), '-M', '-a', '-I', insert_size, '-R', RGinfo, genome_fna, files[1], files[2]]
else:
# BWA can estimate on-the-fly
cmd = [path_to_exe, 'mem', '-t', str(max_processes), '-M', '-a', '-R', RGinfo, genome_fna, files[1], files[2]]
out_sam = _os.path.sep.join([local_alns_path_genome, '%s__%s.sam' % (pairname, self.genome_id)])
if not _os.path.exists(out_sam) or force:
print('Called: "%s"' % ' '.join(cmd))
with open(out_sam, "wb") as out:
_subprocess.call(cmd, stdout = out)
else:
print('Found:')
print(out_sam)
print('use "force = True" to overwrite')
print(' '.join(cmd))
aligned_read_files[pairname] = out_sam
self.aligned_read_files = aligned_read_files
def trim(self, path_to_exe=False, force=False, max_cpus=-1):
if not path_to_exe:
exe_sickle = _get_exe_path('sickle')
else:
exe_sickle = _os.path.sep.join(path_to_exe)
e1 = 'Could not find "adaptorcut_read_files" attribute. \
Before quality score trimming, reads must be cleaned of \
library preparation sequences. Please run cutAdaptors() \
method on this Reads instance.'
assert hasattr(self, 'adaptorcut_read_files'), e1
e2 = 'Could not find %s. Either run cutAdaptors() again \
or ensure file exists'
for pairname, files in self.adaptorcut_read_files.items():
assert _os.path.exists(files[1]), e2 % files[1]
assert _os.path.exists(files[1]), e2 % files[1]
trimmed_read_files = {}
print(sorted(self.adaptorcut_read_files))
cmds = []
processed_paths_to_do = []
for pairname, files in self.adaptorcut_read_files.items():
processed_path_1 = insert_suffix(files[1], '_qual')
processed_path_2 = insert_suffix(files[2], '_qual')
processed_path_s = insert_suffix(files[2], '_singletons_qual')
# Illumina quality using CASAVA >= 1.8 is Sanger encoded
QSscore_scale = 'sanger'
cmd = [
exe_sickle,
'pe',
'-f',
files[1],
'-r',
files[2],
'-t',
QSscore_scale,
'-o',
processed_path_1,
'-p',
processed_path_2,
'-s',
processed_path_s,
# quality 25, length 50 (of 150)
'-q',
'25',
'-l',
'50'
]
if not all([_os.path.exists(processed_path_1),
_os.path.exists(processed_path_2),
_os.path.exists(processed_path_s)]) \
or force:
# collect expected outputs
processed_paths_to_do += [(processed_path_1, processed_path_2,
processed_path_s)]
# collect all the commands to be issued
cmds += [(pairname, cmd)]
else:
print('Found:')
print(processed_path_1)
print(processed_path_2)
print(processed_path_s)
print('use "force = True" to overwrite')
trimmed_read_files[pairname] = {}
trimmed_read_files[pairname][1] = processed_path_1
trimmed_read_files[pairname][2] = processed_path_2
if len(cmds):
max_processes = _decide_max_processes(max_cpus)
processes = {}
### how to combine this which hangs on _os.wait()
for pairname, cmd in cmds:
print('Called: "%s"' % ' '.join(cmd))
# process is key, open file being piped to is value
# baga CollectReads currently includes path in pairname
this_stdout_file = open(pairname + '_sickle.log', "w")
thisprocess = _subprocess.Popen(cmd,
shell=False,
stdout=this_stdout_file)
processes[thisprocess] = this_stdout_file
if len(processes) >= max_processes:
_os.wait()
finished = dict([(p, f) for p, f in processes.items()
if p.poll() is not None])
# close files for finished processes
for process, stdout_file in finished.items():
stdout_file.close()
# update active processes
del processes[process]
# Check if all the child processes were closed
for p in processes:
if p.poll() is None:
p.wait()
fails = []
for (pairname, cmd), (processed_path_1, processed_path_2,
processed_path_s) in zip(cmds,
processed_paths_to_do):
if _os.path.exists(processed_path_1) and _os.path.exists(
processed_path_2):
print('Found:')
print(processed_path_1)
print(processed_path_2)
trimmed_read_files[pairname] = {}
trimmed_read_files[pairname][1] = processed_path_1
trimmed_read_files[pairname][2] = processed_path_2
else:
print('Processing of the following pair seems to have failed')
print(processed_path_1)
print(processed_path_2)
fails += [(processed_path_1, processed_path_2)]
assert len(
fails
) == 0, 'There was a problem finding all of the output from sickle. Try repeating this or an earlier step with the --force option to overwite previous, possibly incomplete, files'
self.trimmed_read_files = trimmed_read_files
def cutAdaptors(self, path_to_exe=False, force=False, max_cpus=-1):
if not path_to_exe:
path_to_exe = _get_exe_path('cutadapt')
adaptorcut_read_files = {}
adaptor_seqs = [
'AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC',
'AGATCGGAAGAGCACACGTCT',
'AGATCGGAAGAGC',
'GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG',
'ACACTCTTTCCCTACACGACGCTCTTCCGATCT',
]
cmds = []
processed_paths_to_do = []
for cnum, (pairname, files) in enumerate(self.read_files.items()):
processed_path_1 = insert_suffix(files[1], '_adpt')
processed_path_2 = insert_suffix(files[2], '_adpt')
# print(files[1], processed_path_1)
# print(files[2], processed_path_2)
# single end
cmd = [path_to_exe] + \
[a for b in [('-a', a) for a in adaptor_seqs] for a in b] + \
['-o', processed_path_1, files[1]]
# paired end
cmd = [path_to_exe] + \
[a for b in [('-a', a) for a in adaptor_seqs] for a in b] + \
[a for b in [('-A', a) for a in adaptor_seqs] for a in b] + \
['-o', processed_path_1, '-p', processed_path_2] + \
[files[1], files[2]]
if not all([_os.path.exists(processed_path_1),
_os.path.exists(processed_path_2)]) \
or force:
# collect expected outputs
processed_paths_to_do += [(processed_path_1, processed_path_2)]
# collect all the commands to be issued
cmds += [(pairname, cmd)]
else:
print('Found:')
print(processed_path_1)
print(processed_path_2)
print('use "force = True" to overwrite')
adaptorcut_read_files[pairname] = {}
adaptorcut_read_files[pairname][1] = processed_path_1
adaptorcut_read_files[pairname][2] = processed_path_2
if len(cmds):
max_processes = _decide_max_processes(max_cpus)
processes = {}
### how to combine this which hangs on _os.wait()
for pairname, cmd in cmds:
print('Called: "%s"' % ' '.join(cmd))
# process is key, open file being piped to is value
# baga CollectReads currently includes path in pairname
this_stdout_file = open(pairname + '_cutadapt.log', "w")
thisprocess = _subprocess.Popen(cmd,
shell=False,
stdout=this_stdout_file)
processes[thisprocess] = this_stdout_file
if len(processes) >= max_processes:
_os.wait()
finished = dict([(p, f) for p, f in processes.items()
if p.poll() is not None])
# close files for finished processes
for process, stdout_file in finished.items():
stdout_file.close()
# update active processes
del processes[process]
# Check if all the child processes were closed
for p in processes:
if p.poll() is None:
p.wait()
fails = []
for (pairname, cmd), (processed_path_1,
processed_path_2) in zip(cmds,
processed_paths_to_do):
if _os.path.exists(processed_path_1) and _os.path.exists(
processed_path_2):
print('Found:')
print(processed_path_1)
print(processed_path_2)
adaptorcut_read_files[pairname] = {}
adaptorcut_read_files[pairname][1] = processed_path_1
adaptorcut_read_files[pairname][2] = processed_path_2
else:
print('Processing of the following pair seems to have failed')
print(processed_path_1)
print(processed_path_2)
fails += [(processed_path_1, processed_path_2)]
assert len(
fails
) == 0, 'There was a problem finding all of the output from cutadapt. Try repeating this or an eralier step with the --force option to overwite previous, possibly incomplete, files'
self.adaptorcut_read_files = adaptorcut_read_files
def IndelRealignGATK(self,
jar=[
'external_programs', 'GenomeAnalysisTK',
'GenomeAnalysisTK.jar'
],
picard_jar=False,
samtools_exe=False,
use_java='java',
force=False,
mem_num_gigs=2,
max_cpus=-1):
# GATK is manually downloaded by user and placed in folder of their choice
jar = _os.path.sep.join(jar)
if not picard_jar:
picard_jar = _get_jar_path('picard')
if not samtools_exe:
samtools_exe = _get_exe_path('samtools')
genome_fna = 'genome_sequences/{}.fna'.format(self.genome_id)
e1 = 'Could not find "paths_to_BAMs_dd_si" attribute. Before starting GATK analysis, read alignments must have duplicates removed. Please run: .toBAMS(), .removeDuplicates(), .sortIndexBAMs() methods on this SAMs instance, or --deduplicate if using baga_cli.py.'
assert hasattr(self, 'paths_to_BAMs_dd_si'), e1
e2 = 'Could not find %s. Please ensure file exists'
for BAM in self.paths_to_BAMs_dd_si:
assert _os.path.exists(BAM), e2 % BAM
# always (re)generate dict in case of upstream changes in data
print('Creating sequence dictionary for %s' % genome_fna)
_subprocess.call([
use_java, '-jar', picard_jar, 'CreateSequenceDictionary', 'R=',
genome_fna, 'O=', genome_fna[:-4] + '.dict'
])
# always (re)index in case of upstream changes in data
print('Writing index files for %s' % genome_fna)
_subprocess.call([samtools_exe, 'faidx', genome_fna])
processes = set()
max_processes = _decide_max_processes(max_cpus)
for BAM in self.paths_to_BAMs_dd_si:
intervals = BAM[:-4] + '.intervals'
if not _os.path.exists(intervals) or force:
cmd = [
use_java,
'-Xmx%sg' % mem_num_gigs, '-jar', jar, '-T',
'RealignerTargetCreator', '-R', genome_fna, '-I', BAM,
'-o', intervals
] #, '--validation_strictness', 'LENIENT']
print(' '.join(map(str, cmd)))
processes.add(_subprocess.Popen(cmd, shell=False))
if len(processes) >= max_processes:
(pid, exit_status) = _os.wait()
processes.difference_update(
[p for p in processes if p.poll() is not None])
else:
print('Found:')
print(intervals)
print('use "force = True" to overwrite')
# Check if all the child processes were closed
for p in processes:
if p.poll() is None:
p.wait()
paths_to_BAMs_dd_si_ra = []
for BAM in self.paths_to_BAMs_dd_si:
intervals = BAM[:-4] + '.intervals'
bam_out = BAM[:-4] + '_realn.bam'
if not _os.path.exists(bam_out) or force:
cmd = [
use_java, '-Xmx4g', '-jar', jar, '-T', 'IndelRealigner',
'-R', genome_fna, '-I', BAM, '-targetIntervals', intervals,
'-o', bam_out, '--filter_bases_not_stored'
]
print(' '.join(map(str, cmd)))
processes.add(_subprocess.Popen(cmd, shell=False))
if len(processes) >= max_processes:
_os.wait()
processes.difference_update(
[p for p in processes if p.poll() is not None])
else:
print('Found:')
print(bam_out)
print('use "force = True" to overwrite')
paths_to_BAMs_dd_si_ra += [bam_out]
for p in processes:
if p.poll() is None:
p.wait()
# the last list of BAMs in ready_BAMs is input for CallgVCFsGATK
# both IndelRealignGATK and recalibBaseScoresGATK put here
self.ready_BAMs = [paths_to_BAMs_dd_si_ra]
def align(self,
insert_size=False,
path_to_exe=False,
local_alns_path=['alignments'],
force=False,
max_cpus=-1):
if not path_to_exe:
path_to_exe = _get_exe_path('bwa')
# write genome sequence to a fasta file
try:
_os.makedirs('genome_sequences')
except OSError:
pass
genome_fna = 'genome_sequences/%s.fna' % self.genome_id
_SeqIO.write(
_SeqRecord(_Seq(self.genome_sequence.tostring()),
id=self.genome_id), genome_fna, 'fasta')
# make folder for alignments (BAMs)
local_alns_path = _os.path.sep.join(local_alns_path)
if not _os.path.exists(local_alns_path):
_os.makedirs(local_alns_path)
# make a subdir for this genome
local_alns_path_genome = _os.path.sep.join(
[local_alns_path, self.genome_id])
if not _os.path.exists(local_alns_path_genome):
_os.makedirs(local_alns_path_genome)
max_processes = _decide_max_processes(max_cpus)
e1 = 'Could not find "read_files" attribute. Before aligning to genome, reads must be quality score trimmed. Please run trim() method on this Reads instance.'
assert hasattr(self, 'read_files'), e1
e2 = 'Could not find %s. Either run trim() again or ensure file exists'
for pairname, files in self.read_files.items():
assert _os.path.exists(files[1]), e2 % files[1]
assert _os.path.exists(files[2]), e2 % files[2]
# always (re)index in case of upstream changes in data
print('Writing BWA index files for %s' % genome_fna)
_subprocess.call([path_to_exe, 'index', genome_fna])
aligned_read_files = {}
for pairname, files in self.read_files.items():
RGinfo = r"@RG\tID:%s\tSM:%s\tPL:ILLUMINA" % (pairname, pairname)
if insert_size:
cmd = [
path_to_exe, 'mem', '-t',
str(max_processes), '-M', '-a', '-I', insert_size, '-R',
RGinfo, genome_fna, files[1], files[2]
]
else:
# BWA can estimate on-the-fly
cmd = [
path_to_exe, 'mem', '-t',
str(max_processes), '-M', '-a', '-R', RGinfo, genome_fna,
files[1], files[2]
]
out_sam = _os.path.sep.join([
local_alns_path_genome,
'%s__%s.sam' % (pairname, self.genome_id)
])
if not _os.path.exists(out_sam) or force:
print('Called: "%s"' % ' '.join(cmd))
with open(out_sam, "wb") as out:
_subprocess.call(cmd, stdout=out)
else:
print('Found:')
print(out_sam)
print('use "force = True" to overwrite')
print(' '.join(cmd))
aligned_read_files[pairname] = out_sam
self.aligned_read_files = aligned_read_files
def generateReads(self, path_to_exe = False,
paths_to_genomes = False,
readcov = 60,
readlen = 100,
fraglen = 350,
sterrfraglen = 20,
model = 4,
max_cpus = -1):
'''
Call GemSIM to generate reads
Need to have written genome sequences to generate from, possibly with
generated SNPs, small indels and large deletions.
'''
#max_cpus etc
if paths_to_genomes:
use_genomes = sorted(paths_to_genomes)
elif hasattr(self, 'written_genomes'):
use_genomes = sorted(self.written_genomes)
else:
raise ValueError('provide either paths_to_genomes or generate some then .writeSequences()')
if not path_to_exe:
path_to_exe = _get_exe_path('gemsim')
comment2 = '''
to generate reads put GemSIM v1.6 into subfolder GemSIM_v1.6 and issue these commands:
GemSIM_v1.6/GemReads.py -r LESB58_for_GemSim_01.fasta -n 1980527 -l d -u 350 -s 20 -m GemSIM_v1.6/models/ill100v4_p.gzip -c -q 33 -p -o GemSimLESB58_01
'''
num_pairs = len(self.genome.sequence) * readcov / (readlen*2)
if model == 4:
path_to_model = _os.path.sep.join(path_to_exe.split(_os.path.sep)[:-1] + ['models','ill100v4_p.gzip'])
elif model == 5:
path_to_model = _os.path.sep.join(path_to_exe.split(_os.path.sep)[:-1] + ['models','ill100v5_p.gzip'])
print('Using error model: {}'.format(path_to_model))
print('Generating {:,} {}bp read pairs for {}x coverage depth of a {}bp genome ({})'.format(
num_pairs, readlen, readcov, len(self.genome.sequence), self.genome.id))
processes = set()
max_processes = _decide_max_processes( max_cpus )
import time
start = time.time()
out_raw = []
for i,genome_in in enumerate(use_genomes):
# could use per genome length . . less consistent than using reference
# genome_len = len(_SeqIO.read(genome_in,'fasta').seq)
# num_pairs = genome_len * readcov / (readlen*2)
outprefix = 'GemSim_{}_{:02d}'.format(self.genome.id, i+1)
cmd = [path_to_exe,
'-r', genome_in,
'-n', num_pairs,
'-l', 'd', '-u', fraglen, '-s', sterrfraglen,
'-m', path_to_model,
'-c',
'-q', 33, '-p',
'-o', outprefix]
out_raw += [outprefix+'_fir.fastq', outprefix+'_sec.fastq']
# this would be better to rename and compress all in one
# maybe as a shell script? Then resuming (--force) would be easier.
if _os.path.exists(outprefix+'_fir.fastq') and \
_os.path.exists(outprefix+'_sec.fastq'):
print('Found output for {}_fir.fastq (and sec), not regenerating, '\
'delete these to start from scratch'.format(outprefix))
else:
cmd = map(str,cmd)
print(' '.join(cmd))
processes.add( _subprocess.Popen(cmd, shell=False) )
if len(processes) >= max_processes:
(pid, exit_status) = _os.wait()
processes.difference_update(
[p for p in processes if p.poll() is not None])
# Check if all the child processes were closed
for p in processes:
if p.poll() is None:
p.wait()
missing = []
for o in out_raw:
if not _os.path.exists(o):
missing += [o]
assert len(missing) == 0, 'Could not find:\n{}'.format('\n'.join(missing))
print('all finished after {} minutes'.format(int(round((time.time() - start)/60.0))))
outdir = _os.path.sep.join(['simulated_reads',self.genome.id])
try:
_os.makedirs(outdir)
except OSError:
pass
for o in out_raw:
new = _os.path.sep.join([outdir, o.replace('fir','R1').replace('sec','R2')])
print('{} ==> {}'.format(o, new))
_os.rename(o, new)
cmd = ['gzip', new]
print(' '.join(cmd))
_subprocess.call(cmd)
def generateReads(self,
path_to_exe=False,
paths_to_genomes=False,
readcov=60,
readlen=100,
fraglen=350,
sterrfraglen=20,
model=4,
max_cpus=-1):
'''
Call GemSIM to generate reads
Need to have written genome sequences to generate from, possibly with
generated SNPs, small indels and large deletions.
'''
#max_cpus etc
if paths_to_genomes:
use_genomes = sorted(paths_to_genomes)
elif hasattr(self, 'written_genomes'):
use_genomes = sorted(self.written_genomes)
else:
raise ValueError(
'provide either paths_to_genomes or generate some then .writeSequences()'
)
if not path_to_exe:
path_to_exe = _get_exe_path('gemsim')
comment2 = '''
to generate reads put GemSIM v1.6 into subfolder GemSIM_v1.6 and issue these commands:
GemSIM_v1.6/GemReads.py -r LESB58_for_GemSim_01.fasta -n 1980527 -l d -u 350 -s 20 -m GemSIM_v1.6/models/ill100v4_p.gzip -c -q 33 -p -o GemSimLESB58_01
'''
num_pairs = len(self.genome.sequence) * readcov / (readlen * 2)
if model == 4:
path_to_model = _os.path.sep.join(
path_to_exe.split(_os.path.sep)[:-1] +
['models', 'ill100v4_p.gzip'])
elif model == 5:
path_to_model = _os.path.sep.join(
path_to_exe.split(_os.path.sep)[:-1] +
['models', 'ill100v5_p.gzip'])
print('Using error model: {}'.format(path_to_model))
print(
'Generating {:,} {}bp read pairs for {}x coverage depth of a {}bp genome ({})'
.format(num_pairs, readlen, readcov, len(self.genome.sequence),
self.genome.id))
processes = set()
max_processes = _decide_max_processes(max_cpus)
import time
start = time.time()
out_raw = []
for i, genome_in in enumerate(use_genomes):
# could use per genome length . . less consistent than using reference
# genome_len = len(_SeqIO.read(genome_in,'fasta').seq)
# num_pairs = genome_len * readcov / (readlen*2)
outprefix = 'GemSim_{}_{:02d}'.format(self.genome.id, i + 1)
cmd = [
path_to_exe, '-r', genome_in, '-n', num_pairs, '-l', 'd', '-u',
fraglen, '-s', sterrfraglen, '-m', path_to_model, '-c', '-q',
33, '-p', '-o', outprefix
]
out_raw += [outprefix + '_fir.fastq', outprefix + '_sec.fastq']
# this would be better to rename and compress all in one
# maybe as a shell script? Then resuming (--force) would be easier.
if _os.path.exists(outprefix+'_fir.fastq') and \
_os.path.exists(outprefix+'_sec.fastq'):
print('Found output for {}_fir.fastq (and sec), not regenerating, '\
'delete these to start from scratch'.format(outprefix))
else:
cmd = map(str, cmd)
print(' '.join(cmd))
processes.add(_subprocess.Popen(cmd, shell=False))
if len(processes) >= max_processes:
(pid, exit_status) = _os.wait()
processes.difference_update(
[p for p in processes if p.poll() is not None])
# Check if all the child processes were closed
for p in processes:
if p.poll() is None:
p.wait()
missing = []
for o in out_raw:
if not _os.path.exists(o):
missing += [o]
assert len(missing) == 0, 'Could not find:\n{}'.format(
'\n'.join(missing))
print('all finished after {} minutes'.format(
int(round((time.time() - start) / 60.0))))
outdir = _os.path.sep.join(['simulated_reads', self.genome.id])
try:
_os.makedirs(outdir)
except OSError:
pass
for o in out_raw:
new = _os.path.sep.join(
[outdir, o.replace('fir', 'R1').replace('sec', 'R2')])
print('{} ==> {}'.format(o, new))
_os.rename(o, new)
cmd = ['gzip', new]
print(' '.join(cmd))
_subprocess.call(cmd)