def fetchMhMismatchFrequencies(dirname,
outdir='mh_mismatch_indel_frequencies'):
if not os.path.isdir(outdir): os.makedirs(outdir)
if isOldLib(dirname): raise Exception('Old Lib not supported')
mh_exp_indels_file = getHighDataDir() + '/mh_mismatch_indels.txt'
fout = io.open(outdir + '/' + getDirLabel(dirname) + '.txt', 'w')
hdr_str = '\t'.join([
'\t'.join([
x + ' Indel Reads in ' + y for x in
['Orig', 'Left Mut', 'Right Mut', 'Merged Mut1', 'Merged Mut2']
]) for y in ['Mut', 'Orig']
])
f = io.open(mh_exp_indels_file)
rdr = csv.DictReader(f, delimiter='\t')
fout.write(u'%s\t%s\tMut Non-Null Reads\tOrig Non-Null Reads\n' %
('\t'.join(rdr.fieldnames), hdr_str))
for row in rdr:
#Load Indel Profiles for both the original and mutated micrhomology forms
mut_oligo_id = row['Oligo ID'].replace('_', '')
orig_oligo_id = row['Mapped Oligo Id'].replace('_', '')
mut_filepath, mut_filename = getFileForOligoIdx(
getOligoIdxFromId(mut_oligo_id), ext='_mappedindelsummary.txt')
orig_filepath, orig_filename = getFileForOligoIdx(
getOligoIdxFromId(orig_oligo_id), ext='_mappedindelsummary.txt')
p_mut, p_orig = {}, {}
stats_mut = readSummaryToProfile(dirname + '/mapped_reads/' +
mut_filepath + '/' + mut_filename,
p_mut,
oligoid=mut_oligo_id)
stats_orig = readSummaryToProfile(dirname + '/mapped_reads/' +
orig_filepath + '/' + orig_filename,
p_orig,
oligoid=orig_oligo_id)
indels = [
row['Orig Indel'], row['Left Mut-MH Indel'],
row['Right Mut-MH Indel'], row['Merge Mut 1 Indel'],
row['Merge Mut 2 Indel']
]
reads = lambda indel, profile: profile[indel] if (indel in profile and
indel != '') else 0
mut_read_str = '\t'.join(
['%d' % reads(indel, p_mut) for indel in indels])
orig_read_str = '\t'.join(
['%d' % reads(indel, p_orig) for indel in indels])
str_args = ('\t'.join([row[col] for col in rdr.fieldnames
]), mut_read_str, orig_read_str,
stats_mut[0] - stats_mut[2], stats_orig[0] - stats_orig[2])
fout.write(u'%s\t%s\t%s\t%d\t%d\n' % str_args)
f.close()
fout.close()
def get_data(self) -> WGEData:
reads_file = tempfile.mkstemp()[1]
profile_file = tempfile.mkstemp()[1]
r = requests.get(self.filename, allow_redirects=True)
with open(reads_file, 'w') as f:
f.write(r.text)
r = requests.get(self.filename.replace("_predicted_rep_reads.txt", "_predicted_mapped_indel_summary.txt"),
allow_redirects=True)
with open(profile_file, 'w') as f:
f.write(r.text)
crispr_line_info = get_guide_info_from_oligo_id(profile_file, self.oligo_id)
profile = {}
readSummaryToProfile(profile_file, profile, oligoid=self.oligo_id, remove_wt=False)
return WGEData(reads_file, profile_file, profile, crispr_line_info)
def read_profile(obj):
reads_file = tempfile.mkstemp()[1]
profile_file = tempfile.mkstemp()[1]
r = requests.get(obj['filename'], allow_redirects=True)
with open(reads_file, 'w') as f:
f.write(r.text)
r = requests.get(obj['filename'].replace(
"_predicted_rep_reads.txt", "_predicted_mapped_indel_summary.txt"),
allow_redirects=True)
with open(profile_file, 'w') as f:
f.write(r.text)
profile = {}
readSummaryToProfile(profile_file,
profile,
oligoid=obj['oligo_id'],
remove_wt=False)
return reads_file, profile_file, profile
def loadProfilePair(old_id, new_id):
p_old, p_new = {}, {}
old_file, new_file = getFileSuffix(old_id), getFileSuffix(new_id)
mut_reads_old, mut_reads_new = 0, 0
for new_dir in new_dirs:
acc, pacc, null = readSummaryToProfile(new_dir + 'mapped_reads/' +
new_file,
p_new,
oligoid=new_id)
mut_reads_new += (acc - null)
for old_dir in old_dirs:
acc, pacc, null = readSummaryToProfile(old_dir + 'mapped_reads/' +
old_file,
p_old,
oligoid=old_id)
mut_reads_old += (acc - null)
return p_old, p_new, mut_reads_old, mut_reads_new
def loadProfilesSeparately(old_id, new_id):
p_olds, p_news, old_sep_mr, new_sep_mr = [{}, {}], [{}, {}], [0, 0], [0, 0]
old_file, new_file = getSummaryFileSuffix(old_id), getSummaryFileSuffix(
new_id)
for new_dir in [getHighDataDir() + '/' + x for x in new_dirs]:
idx = 0 if '800' in new_dir else 1
acc, pacc, null = readSummaryToProfile(new_dir + '/mapped_reads/' +
new_file,
p_news[idx],
oligoid=new_id)
new_sep_mr[idx] += acc - null
for old_dir in [getHighDataDir() + '/' + x for x in old_dirs]:
idx = 0 if '800' in old_dir else 1
acc, pacc, null = readSummaryToProfile(old_dir + '/mapped_reads/' +
old_file,
p_olds[idx],
oligoid=old_id)
old_sep_mr[idx] += acc - null
return p_olds, p_news, old_sep_mr, new_sep_mr
def loadSeparateProfilePairs(old_id, new_id):
old_ps, new_ps = [], []
old_file, new_file = getFileSuffix(old_id), getFileSuffix(new_id)
for new_dir in new_dirs:
p_new, mut_reads_new = {}, 0
acc, pacc, null = readSummaryToProfile(new_dir + 'mapped_reads/' +
new_file,
p_new,
oligoid=new_id)
mut_reads_new += (acc - null)
new_ps.append(p_new)
for old_dir in old_dirs:
p_old, mut_reads_old = {}, 0
acc, pacc, null = readSummaryToProfile(old_dir + 'mapped_reads/' +
old_file,
p_old,
oligoid=old_id)
mut_reads_old += (acc - null)
old_ps.append(p_old)
return old_ps, new_ps
def compileGenIndelReads(gen_indel_dir='generated_indels',
out_dir='reads_for_gen_indels_all_samples',
sample_dirs=[]):
if not os.path.isdir(out_dir): os.mkdir(out_dir)
for gen_file in os.listdir(gen_indel_dir):
oligo_id = gen_file.split('_')[0]
oligo_idx = getOligoIdxFromId(oligo_id)
oligo_subdir, sum_filename = getFileForOligoIdx(
oligo_idx, ext='_mappedindelsummary.txt')
out_subdir = out_dir + '/' + oligo_subdir
if not os.path.isdir(out_subdir): os.mkdir(out_subdir)
#Read all profiles for this oligo
profiles, mut_read_totals = [], []
for dirname in sample_dirs:
profiles.append({})
filename = getHighDataDir(
) + '/' + dirname + '/mapped_reads/' + oligo_subdir + '/' + sum_filename
stats = readSummaryToProfile(filename,
profiles[-1],
oligoid=oligo_id)
mut_read_totals.append('%d' % (stats[0] - stats[2]))
#Compile reads for each indel across all samples
f = io.open(gen_indel_dir + '/' + gen_file)
fout = io.open(out_subdir + '/%s_gen_indel_reads.txt' % oligo_id, 'w')
fout.write(f.readline()) #Git commit
fout.write(u'Indel\tDetails\t%s\n' %
'\t'.join([getDirLabel(x) for x in sample_dirs]))
fout.write(u'All Mutated\t[]\t%s\n' % '\t'.join(mut_read_totals))
for toks in csv.reader(f, delimiter='\t'):
indel, indel_details = toks[0], toks[2]
read_str = '\t'.join(
['%d' % (p1[indel] if indel in p1 else 0) for p1 in profiles])
fout.write(u'%s\t%s\t%s\n' % (indel, indel_details, read_str))
fout.close()
f.close()
if len(sys.argv) > 3: more_indels = eval(sys.argv[3])
if more_indels: out_dir = createResultDirectory(high_dir + '/more_indel_summaries',subdir)
else: out_dir = createResultDirectory(high_dir + '/most_common_indel_summaries', subdir)
fout = io.open(out_dir + '/' + subdir.split('/')[-1] + '.txt', 'w')
oligo_lookup = loadExpOligoLookup(subdir)
#For each Oligo, summarise details of its most common indel
fout.write(u'Oligo Id\tMost Common Indel\tLeft\tRight\tCentral\tType\tSize\tMCI Reads\tTotal reads\tMicrohomology Sequence\n')
sum_files = getIndelSummaryFiles(subdir)
for filename in sum_files:
file_prefix = filename.split('/')[-1][:-23]
oligo_details = {x[0]: x[1:] for x in oligo_lookup[file_prefix]}
oligo_ids = getOligoIdsFromFile(filename)
for id in oligo_ids:
#Read in the profile (if it exists)
p1 = {}
stats1 = readSummaryToProfile(filename, p1, oligoid=getShortOligoId(id))
if len(p1) == 0 or p1.keys() == ['-']:
continue
#Compute and summarise its MCI details
writeMCISummary(fout, id, p1, stats1, oligo_details[id], more_indels)
fout.close()
dir1_files = getIndelSummaryFiles(dirname1 + '/mapped_reads/' + subdir, withpath=False)
dir2_files = getIndelSummaryFiles(dirname2 + '/mapped_reads/' + subdir, withpath=False)
common_files = set(dir1_files).intersection(set(dir2_files))
for filename in common_files:
filename1 = dirname1 + '/mapped_reads/' + subdir + '/' + filename
filename2 = dirname2 + '/mapped_reads/' + subdir + '/' + filename
oligo_ids1 = getOligoIdsFromFile( filename1 )
oligo_ids2 = getOligoIdsFromFile( filename2 )
common_oligos = set(oligo_ids1).intersection(set(oligo_ids2))
for oligo_id in common_oligos:
profile1, profile2 = {}, {}
num_reads1, perc_acc1, nonull1 = readSummaryToProfile(filename1, profile1, oligoid=oligo_id)
num_reads2, perc_acc2, nonull2 = readSummaryToProfile(filename2, profile2, oligoid=oligo_id)
ns1, ns2 = len(profile1), len(profile2)
if remove_largeI:
profile1 = filterLargeI(profile1)
profile2 = filterLargeI(profile2)
ent1a, ent2a = entropy(profile1,True), entropy(profile2,True)
poverlap = percentOverlap( profile1, profile2, True )
score1 = symmetricKL( profile1, profile2, False )
score2 = symmetricKL( profile1, profile2, True )
ent1b, ent2b = entropy(profile1,True), entropy(profile2,True) #Since comparing the profiles appends missing states to both profiles
def compareOverbeekProfiles(
selected_overbeek_id=None,
pred_results_dir='../indel_prediction/model_testing'):
new_dirs = [
'ST_June_2017/data/K562_800x_LV7A_DPI7/mapped_reads/Oligos_71',
'ST_June_2017/data/K562_800x_LV7A_DPI10/mapped_reads/Oligos_71',
'ST_June_2017/data/K562_800x_LV7B_DPI7/mapped_reads/Oligos_71',
'ST_June_2017/data/K562_800x_LV7B_DPI10/mapped_reads/Oligos_71',
'ST_June_2017/data/K562_1600x_LV7B_DPI5/mapped_reads/Oligos_71',
'ST_Feb_2018/data/CAS9_12NA_1600X_DPI7/mapped_reads/Oligos_71'
]
#Old Samples
old_dirs = [
'ST_June_2017/data/K562_1600x_6OA_DPI5/mapped_reads/Oligos_71',
'ST_June_2017/data/K562_1600x_6OA_DPI7/mapped_reads/Oligos_71',
'ST_April_2017/data/K562_800x_6OA_DPI3_Old7/mapped_reads/Oligos_71',
'ST_April_2017/data/K562_800x_6OA_DPI7_Old8/mapped_reads/Oligos_71',
'ST_April_2017/data/K562_800x_6OA_DPI10_Old9/mapped_reads/Oligos_71',
'ST_April_2017/data/K562_800x_6OB_DPI3_Old10/mapped_reads/Oligos_71',
'ST_April_2017/data/K562_800x_6OB_DPI7_Old11/mapped_reads/Oligos_71',
'ST_April_2017/data/K562_800x_6OB_DPI10_Old12/mapped_reads/Oligos_71'
]
remove_long_indels = False
remove_wt, wt_thresh = True, 3.0
mappings = loadMappings()
all_overbeek_profiles, all_new_profiles, all_old_profiles, all_our_profiles, sel_overbeek_ids,oldnew_overbeek_ids, old_ids, new_ids = [],[],[],[], [],[],[],[]
overbeek_inframes, ours_inframes, oof_sel_overbeek_ids = [], [], []
kls, kls_old, kls_new, log_reads, overbeek_ids, above30_percentages, log_reads_new, log_reads_old, min_log_reads = [],[],[],[],[],[],[],[], []
for idx in range(1, 97):
overbeek_id = 'Overbeek%d' % idx
if selected_overbeek_id is not None and selected_overbeek_id != overbeek_id:
continue
if overbeek_id not in mappings:
continue
overbeek_filename = getHighDataDir(
) + '/overbeek_fastq_files/' + overbeek_id + '_mappedindelsummary.txt'
p1, p1_new, p1_old, o1, rep_reads1, rep_reads2 = {}, {}, {}, {}, {}, {}
nreads2, nreads1, nreads_old, nreads_new, nnull_old, nnull_new, nnull1, nnull2 = 0, 0, 0, 0, 0, 0, 0, 0
#Read the overbreek profile
numread2, perc_accept2, num_null2 = readSummaryToProfile(
overbeek_filename,
o1,
oligoid=overbeek_id,
remove_long_indels=remove_long_indels,
remove_wt=False)
if selected_overbeek_id is not None:
fetchRepresentativeCleanReads(
getHighDataDir() + '/overbeek_fastq_files/' + overbeek_id +
'_mappedindelprofiles.txt',
rep_reads2,
oligoid=overbeek_id)
pam_loc2, pam_dir2 = getNullTargetPamDetails(
getHighDataDir() + '/overbeek_control_fastq_files/' +
overbeek_id + '_exptargets.txt',
oligoid=overbeek_id)
nreads2 += numread2
nnull2 += num_null2
if numread2 == 0: continue
p1_new_reps, p1_old_reps = [{}, {}], [{}, {}]
rr_new_reps, rr_old_reps = [{}, {}], [{}, {}]
#Read all the new and old profiles
pam_loc1, pam_dir1 = None, None
for oligo_id, is_old in mappings[overbeek_id]:
#Read all reads for all our K562 profiles
oligo_idx = eval(oligo_id[5:])
_, oligo_fileprefix = getFileForOligoIdx(oligo_idx, ext='')
oligo_filename = oligo_fileprefix + '_mappedindelsummary.txt'
read_filename = oligo_fileprefix + '_mappedindelprofiles.txt'
exptarget_filename = oligo_fileprefix + '_exptargets.txt'
if is_old:
oligo_dirs, p1_old_new, null_oligo_dir = old_dirs, p1_old, 'ST_April_2017/data/NULL_Old/mapped_reads/Oligos_71'
p1_reps, rr_reps = p1_old_reps, rr_old_reps
else:
oligo_dirs, p1_old_new, null_oligo_dir = new_dirs, p1_new, 'ST_April_2017/data/NULL_New/mapped_reads/Oligos_71'
p1_reps, rr_reps = p1_new_reps, rr_new_reps
for oligo_dir in [getHighDataDir() + '/' + x for x in oligo_dirs]:
nr1, pa1, nn1 = readSummaryToProfile(
oligo_dir + '/' + oligo_filename,
p1_old_new,
oligoid=oligo_id,
remove_long_indels=remove_long_indels,
remove_wt=remove_wt,
wt_thresh=wt_thresh)
numread1, perc_accept1, num_null1 = readSummaryToProfile(
oligo_dir + '/' + oligo_filename,
p1,
oligoid=oligo_id,
remove_long_indels=remove_long_indels,
remove_wt=remove_wt,
wt_thresh=wt_thresh)
if 'DPI7' in oligo_dir:
rep_idx = 0 if '800x' in oligo_dir else 1
nr_rep, pa_rep, nn_rep = readSummaryToProfile(
oligo_dir + '/' + oligo_filename,
p1_reps[rep_idx],
oligoid=oligo_id,
remove_long_indels=remove_long_indels,
remove_wt=remove_wt,
wt_thresh=wt_thresh)
if selected_overbeek_id is not None:
fetchRepresentativeCleanReads(oligo_dir + '/' +
read_filename,
rep_reads1,
oligoid=oligo_id)
if 'DPI7' in oligo_dir:
fetchRepresentativeCleanReads(oligo_dir + '/' +
read_filename,
rr_reps[rep_idx],
oligoid=oligo_id)
if pam_loc1 is None:
pam_loc1, pam_dir1 = getNullTargetPamDetails(
getHighDataDir() + '/' + null_oligo_dir + '/' +
exptarget_filename,
oligoid=oligo_id)
if is_old:
nreads_old += numread1
nnull_old += num_null1
else:
nreads_new += numread1
nnull_new += num_null1
nreads1 += numread1
nnull1 += num_null1
kls.append(symmetricKL(p1, o1, True))
kls_old.append(symmetricKL(p1_old, o1, True))
kls_new.append(symmetricKL(p1_new, o1, True))
log_reads.append(np.log10(nreads1 - nnull1 + 0.5))
log_reads_old.append(np.log10(nreads_old - nnull_old + 0.5))
log_reads_new.append(np.log10(nreads_new - nnull_new + 0.5))
min_log_reads.append(min(log_reads_old[-1], log_reads_new[-1]))
above30_percentages.append(computePercAbove30(o1))
overbeek_ids.append(overbeek_id)
if log_reads[-1] > 2.0:
all_overbeek_profiles.append(o1)
all_our_profiles.append(p1)
sel_overbeek_ids.append(overbeek_id[8:])
if above30_percentages[-1] < 50.0:
oif, oof, _ = fetchIndelSizeCounts(o1)
pif, pof, _ = fetchIndelSizeCounts(p1)
overbeek_inframes.append(oif * 100.0 / (oif + oof))
ours_inframes.append(pif * 100.0 / (pif + pof))
oof_sel_overbeek_ids.append(overbeek_id)
if min_log_reads[-1] > 2.0:
all_new_profiles.append(p1_new)
all_old_profiles.append(p1_old)
oldnew_overbeek_ids.append(overbeek_id)
old_ids.append(
[id for id, is_old in mappings[overbeek_id] if is_old][0])
new_ids.append(
[id for id, is_old in mappings[overbeek_id] if not is_old][0])
try:
print(overbeek_id, [x for (x, y) in mappings[overbeek_id]],
kls[-1], nreads2, nreads1)
except KeyError:
print('Could not find', overbeek_id)
print(mappings)
if selected_overbeek_id is not None:
title = '%s (KL=%.1f)' % (overbeek_id, kls[-1])
labels = [
'Conventional scaffold Rep A', 'Conventional scaffold Rep B',
'Improved scaffold Rep A', 'Improved scaffold Rep B',
'Endogenous Profile'
]
plotProfiles([
p1_old_reps[0], p1_old_reps[1], p1_new_reps[0], p1_new_reps[0],
o1
], [
rr_old_reps[0], rr_old_reps[1], rr_new_reps[0], rr_new_reps[1],
rep_reads2
], [pam_loc1, pam_loc1, pam_loc1, pam_loc1, pam_loc2], [
x == 'REVERSE'
for x in [pam_dir1, pam_dir1, pam_dir1, pam_dir1, pam_dir2]
],
labels,
title=title)
if selected_overbeek_id is None:
plotInFrame(overbeek_inframes, ours_inframes, oof_sel_overbeek_ids,
pred_results_dir)
i = 1
PL.figure(figsize=(5.5, 5))
for thr_l, thr_h in [(0.0, 10.0), (10.0, 20.0), (20.0, 50.0),
(50.0, 90.0), (90.0, 100.0)]:
ydata = [
kl for (kl, a30, id, reads) in zip(kls, above30_percentages,
overbeek_ids, log_reads)
if a30 > thr_l and a30 <= thr_h
]
xdata = [
reads for (kl, a30, id, reads) in zip(kls, above30_percentages,
overbeek_ids, log_reads)
if a30 > thr_l and a30 <= thr_h
]
sel_ids = [
id for (kl, a30, id, reads) in zip(kls, above30_percentages,
overbeek_ids, log_reads)
if a30 > thr_l and a30 <= thr_h
]
PL.plot(xdata,
ydata,
'o',
label='%d-%d%% Deletions > 30' % (thr_l, thr_h))
for x, y, id in zip(xdata, ydata, sel_ids):
if y > 3 and x > 2:
PL.text(x, y, id)
PL.legend()
PL.plot([0, 6], [0.77, 0.77], '--', color='grey')
PL.text(0.1, 0.5, 'Median between our replicates', color='grey')
PL.ylabel('Symmetric KL Divergence', fontsize=12)
PL.xlabel('Log10 Mutated Reads', fontsize=12)
PL.xlim((0, 5.5))
PL.ylim((0, 8))
PL.show(block=False)
saveFig('scatter_KL')
i += 1
print('Median=', np.median(kls), 'Mean KL=', np.mean(kls))
print(len(overbeek_ids))
#Compute pairwise KL between overbeek and ours
N = len(sel_overbeek_ids)
kl_mat = np.zeros((N, N))
for i, o1 in enumerate(all_overbeek_profiles):
for j, p1 in enumerate(all_our_profiles):
kl_mat[i, j] = symmetricKL(o1, p1)
PL.figure(figsize=(8, 6))
PL.imshow(kl_mat,
cmap='hot_r',
vmin=0.0,
vmax=3.0,
interpolation='nearest')
PL.xticks(range(N), sel_overbeek_ids, rotation='vertical', fontsize=6)
PL.yticks(range(N),
sel_overbeek_ids,
rotation='horizontal',
fontsize=6)
PL.xlabel('Synthetic Measurement', fontsize=12)
PL.ylabel('Endogenous Measurement', fontsize=12)
PL.title('KL', fontsize=12)
PL.colorbar()
PL.show(block=False)
saveFig('heatmap_KL')
indel_files = getIndelSummaryFiles(subdir, withpath=False)
for indel_file in indel_files:
oligo_ids = getOligoIdsFromFile(subdir + '/' + indel_file)
mh_loc = '.' if highdir == '.' else highdir + '/ST_June_2017/data'
mh_indels = loadMhExpIndels(mh_loc + '/' + mh_exp_indels_file,
set(oligo_ids))
fout = io.open(outdir + '/' + indel_file[:-23] + '_mhindels.txt',
'w')
for oligo_id in oligo_ids:
profile = {}
acc, pacc, nullr = readSummaryToProfile(subdir + '/' +
indel_file,
profile,
oligoid=oligo_id)
fout.write(u'@@@%s:%d:%d\n' % (oligo_id, acc, acc - nullr))
mhs, indels = mh_indels[oligo_id]
for (mh, indel) in zip(mhs, indels):
left, right, mh_len = mh.split(':')
if indel == 'Unmappable': continue
if indel in profile: nreads = profile[indel]
else: nreads = 0
fout.write(u'%s\t%s\t%s\t%s\t%d\n' %
(left, right, mh_len, indel, nreads))
fout.close()
