def run(opts):
check_options(opts)
samtools = which(opts.samtools)
launch_time = time.localtime()
param_hash = digest_parameters(opts)
reso1 = reso2 = None
if opts.bam1:
mreads1 = path.realpath(opts.bam1)
biases1 = opts.biases1
else:
biases1, mreads1, reso1 = load_parameters_fromdb(
opts.workdir1, opts.jobid1, opts, opts.tmpdb1)
mreads1 = path.join(opts.workdir1, mreads1)
try:
biases1 = path.join(opts.workdir1, biases1)
except AttributeError:
biases1 = None
except TypeError: # Py3
biases1 = None
if opts.bam2:
mreads2 = path.realpath(opts.bam2)
biases2 = opts.biases2
else:
biases2, mreads2, reso2 = load_parameters_fromdb(
opts.workdir2, opts.jobid2, opts, opts.tmpdb2)
mreads2 = path.join(opts.workdir2, mreads2)
try:
biases2 = path.join(opts.workdir2, biases2)
except AttributeError:
biases2 = None
except TypeError: # Py3
biases1 = None
filter_exclude = opts.filter
if reso1 != reso2:
raise Exception('ERROR: differing resolutions between experiments to '
'be merged')
mkdir(path.join(opts.workdir, '00_merge'))
if not opts.skip_comparison:
printime(' - loading first sample %s' % (mreads1))
hic_data1 = load_hic_data_from_bam(mreads1, opts.reso, biases=biases1,
tmpdir=path.join(opts.workdir, '00_merge'),
ncpus=opts.cpus,
filter_exclude=filter_exclude)
printime(' - loading second sample %s' % (mreads2))
hic_data2 = load_hic_data_from_bam(mreads2, opts.reso, biases=biases2,
tmpdir=path.join(opts.workdir, '00_merge'),
ncpus=opts.cpus,
filter_exclude=filter_exclude)
if opts.workdir1 and opts.workdir2:
masked1 = {'valid-pairs': {'count': 0}}
masked2 = {'valid-pairs': {'count': 0}}
else:
masked1 = {'valid-pairs': {'count': sum(hic_data1.values())}}
masked2 = {'valid-pairs': {'count': sum(hic_data2.values())}}
decay_corr_dat = path.join(opts.workdir, '00_merge', 'decay_corr_dat_%s_%s.txt' % (opts.reso, param_hash))
decay_corr_fig = path.join(opts.workdir, '00_merge', 'decay_corr_dat_%s_%s.png' % (opts.reso, param_hash))
eigen_corr_dat = path.join(opts.workdir, '00_merge', 'eigen_corr_dat_%s_%s.txt' % (opts.reso, param_hash))
eigen_corr_fig = path.join(opts.workdir, '00_merge', 'eigen_corr_dat_%s_%s.png' % (opts.reso, param_hash))
printime(' - comparing experiments')
printime(' => correlation between equidistant loci')
corr, _, scc, std, bads = correlate_matrices(
hic_data1, hic_data2, normalized=opts.norm,
remove_bad_columns=True, savefig=decay_corr_fig,
savedata=decay_corr_dat, get_bads=True)
print(' - correlation score (SCC): %.4f (+- %.7f)' % (scc, std))
printime(' => correlation between eigenvectors')
eig_corr = eig_correlate_matrices(hic_data1, hic_data2, normalized=opts.norm,
remove_bad_columns=True, nvect=6,
savefig=eigen_corr_fig,
savedata=eigen_corr_dat)
printime(' => reproducibility score')
reprod = get_reproducibility(hic_data1, hic_data2, num_evec=20, normalized=opts.norm,
verbose=False, remove_bad_columns=True)
print(' - reproducibility score: %.4f' % (reprod))
ncols = len(hic_data1)
else:
ncols = 0
decay_corr_dat = 'None'
decay_corr_fig = 'None'
eigen_corr_dat = 'None'
eigen_corr_fig = 'None'
masked1 = {}
masked2 = {}
corr = eig_corr = scc = std = reprod = 0
bads = {}
# merge inputs
mkdir(path.join(opts.workdir, '03_filtered_reads'))
outbam = path.join(opts.workdir, '03_filtered_reads',
'intersection_%s.bam' % (param_hash))
if not opts.skip_merge:
outbam = path.join(opts.workdir, '03_filtered_reads',
'intersection_%s.bam' % (param_hash))
printime(' - Mergeing experiments')
system(samtools + ' merge -@ %d %s %s %s' % (opts.cpus, outbam, mreads1, mreads2))
printime(' - Indexing new BAM file')
# check samtools version number and modify command line
version = LooseVersion([l.split()[1]
for l in Popen(samtools, stderr=PIPE,
universal_newlines=True).communicate()[1].split('\n')
if 'Version' in l][0])
if version >= LooseVersion('1.3.1'):
system(samtools + ' index -@ %d %s' % (opts.cpus, outbam))
else:
system(samtools + ' index %s' % (outbam))
else:
outbam = ''
finish_time = time.localtime()
save_to_db (opts, mreads1, mreads2, decay_corr_dat, decay_corr_fig,
len(list(bads.keys())), ncols, scc, std, reprod,
eigen_corr_dat, eigen_corr_fig, outbam, corr, eig_corr,
biases1, biases2, masked1, masked2, launch_time, finish_time)
printime('\nDone.')
def run(opts):
check_options(opts)
samtools = which(opts.samtools)
launch_time = time.localtime()
param_hash = digest_parameters(opts)
reso1 = reso2 = None
if opts.bam1:
mreads1 = path.realpath(opts.bam1)
biases1 = opts.biases1
else:
biases1, mreads1, reso1 = load_parameters_fromdb(
opts.workdir1, opts.jobid1, opts, opts.tmpdb1)
mreads1 = path.join(opts.workdir1, mreads1)
try:
biases1 = path.join(opts.workdir1, biases1)
except AttributeError:
biases1 = None
if opts.bam2:
mreads2 = path.realpath(opts.bam2)
biases2 = opts.biases2
else:
biases2, mreads2, reso2 = load_parameters_fromdb(
opts.workdir2, opts.jobid2, opts, opts.tmpdb2)
mreads2 = path.join(opts.workdir2, mreads2)
try:
biases2 = path.join(opts.workdir2, biases2)
except AttributeError:
biases2 = None
filter_exclude = opts.filter
if reso1 != reso2:
raise Exception('ERROR: differing resolutions between experiments to '
'be merged')
mkdir(path.join(opts.workdir, '00_merge'))
if not opts.skip_comparison:
printime(' - loading first sample %s' % (mreads1))
hic_data1 = load_hic_data_from_bam(mreads1, opts.reso, biases=biases1,
tmpdir=path.join(opts.workdir, '00_merge'),
ncpus=opts.cpus,
filter_exclude=filter_exclude)
printime(' - loading second sample %s' % (mreads2))
hic_data2 = load_hic_data_from_bam(mreads2, opts.reso, biases=biases2,
tmpdir=path.join(opts.workdir, '00_merge'),
ncpus=opts.cpus,
filter_exclude=filter_exclude)
decay_corr_dat = path.join(opts.workdir, '00_merge', 'decay_corr_dat_%s_%s.txt' % (opts.reso, param_hash))
decay_corr_fig = path.join(opts.workdir, '00_merge', 'decay_corr_dat_%s_%s.png' % (opts.reso, param_hash))
eigen_corr_dat = path.join(opts.workdir, '00_merge', 'eigen_corr_dat_%s_%s.txt' % (opts.reso, param_hash))
eigen_corr_fig = path.join(opts.workdir, '00_merge', 'eigen_corr_dat_%s_%s.png' % (opts.reso, param_hash))
printime(' - comparing experiments')
printime(' => correlation between equidistant loci')
corr, _, scc, std, bads = correlate_matrices(
hic_data1, hic_data2, normalized=opts.norm,
remove_bad_columns=True, savefig=decay_corr_fig,
savedata=decay_corr_dat, get_bads=True)
print ' - correlation score (SCC): %.4f (+- %.7f)' % (scc, std)
printime(' => correlation between eigenvectors')
eig_corr = eig_correlate_matrices(hic_data1, hic_data2, normalized=opts.norm,
remove_bad_columns=True, nvect=6,
savefig=eigen_corr_fig,
savedata=eigen_corr_dat)
printime(' => reproducibility score')
reprod = get_reproducibility(hic_data1, hic_data2, num_evec=20, normalized=opts.norm,
verbose=False, remove_bad_columns=True)
print ' - reproducibility score: %.4f' % (reprod)
ncols = len(hic_data1)
else:
ncols = 0
decay_corr_dat = 'None'
decay_corr_fig = 'None'
eigen_corr_dat = 'None'
eigen_corr_fig = 'None'
corr = eig_corr = 0
bads = {}
# merge inputs
mkdir(path.join(opts.workdir, '03_filtered_reads'))
outbam = path.join(opts.workdir, '03_filtered_reads',
'intersection_%s.bam' % (param_hash))
printime(' - Mergeing experiments')
system(samtools + ' merge -@ %d %s %s %s' % (opts.cpus, outbam, mreads1, mreads2))
printime(' - Indexing new BAM file')
# check samtools version number and modify command line
version = LooseVersion([l.split()[1]
for l in Popen(samtools, stderr=PIPE).communicate()[1].split('\n')
if 'Version' in l][0])
if version >= LooseVersion('1.3.1'):
system(samtools + ' index -@ %d %s' % (opts.cpus, outbam))
else:
system(samtools + ' index %s' % (outbam))
finish_time = time.localtime()
save_to_db (opts, mreads1, mreads2, decay_corr_dat, decay_corr_fig,
len(bads.keys()), ncols, scc, std, reprod,
eigen_corr_dat, eigen_corr_fig, outbam, corr, eig_corr,
biases1, biases2, launch_time, finish_time)
printime('\nDone.')