def main(args):
if args.mapping:
tdict = {}
table = utils.tab_line_gen(args.mapping)
header = table.next()
for t in table:
d = dict(zip(header, t))
tdict[d[args.key]] = d
else:
# Lookup of any key in tdict returns a dictionary where the value of 'name' is ''
tdict = defaultdict(lambda: {'name': ''})
gtf = utils.tab_line_gen(args.infile)
for g in gtf:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";', g[8]))
assert 'locus' not in attrd
if g[1] == 'merged':
newname = tdict[attrd['name']][args.value]
if newname == '':
n1, n2 = attrd['name'].split('_')
newname = '%s_%s_%s' % (n1, g[0].strip('chr'), n2)
g[8] += ' locus "%s";' % newname
print >> args.outfile, '\t'.join(g)
else:
newname = tdict[attrd['gene_id']][args.value]
if newname == '':
n1, n2 = attrd['gene_id'].split('_')
newname = '%s_%s_%s' % (n1, g[0].strip('chr'), n2)
g[8] += ' locus "%s";' % newname
print >> args.outfile, '\t'.join(g)
def main(args):
if args.mapping:
tdict = {}
table = utils.tab_line_gen(args.mapping)
header = table.next()
for t in table:
d = dict(zip(header,t))
tdict[d[args.key]] = d
else:
# Lookup of any key in tdict returns a dictionary where the value of 'name' is ''
tdict = defaultdict(lambda:{'name':''})
gtf = utils.tab_line_gen(args.infile)
for g in gtf:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";',g[8]))
assert 'locus' not in attrd
if g[1]=='merged':
newname = tdict[attrd['name']][args.value]
if newname == '':
n1,n2 = attrd['name'].split('_')
newname = '%s_%s_%s' % (n1, g[0].strip('chr'), n2)
g[8] += ' locus "%s";' % newname
print >>args.outfile, '\t'.join(g)
else:
newname = tdict[attrd['gene_id']][args.value]
if newname == '':
n1,n2 = attrd['gene_id'].split('_')
newname = '%s_%s_%s' % (n1, g[0].strip('chr'), n2)
g[8] += ' locus "%s";' % newname
print >>args.outfile, '\t'.join(g)
def main(args):
combined_gtf = [GTFLine(l) for l in utils.tab_line_gen(args.infile)]
if args.prefix is None:
prefix = Counter(g.attr['locus'].split('_')[0] for g in combined_gtf).most_common()[0][0]
else:
prefix = args.prefix
namemap = {}
if args.cytoband:
byband = defaultdict(list)
p1 = Popen('bedtools intersect -wo -a - -b %s' % args.cytoband, shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE)
o,e = p1.communicate(input='\n'.join(str(g) for g in combined_gtf if g.feature.startswith('span')))
for l in utils.tab_line_gen(o.strip('\n').split('\n')):
g1 = GTFLine(l[:9])
g2 = GTFLine(l[9:-1])
band = '%s%s' % (g2.chrom.strip('chr'),g2.attr['gene_id'])
byband[band].append(g1)
for band, locs in byband.iteritems():
if len(locs) == 1:
namemap[locs[0].attr['locus']] = '%s_%s' % (prefix, band)
else:
locs.sort(key=lambda x:x.start)
for i,loc in enumerate(locs):
namemap[loc.attr['locus']] = '%s_%s%s' % (prefix, band, someletters[i])
else:
for g in combined_gtf:
namemap[g.attr['locus']] = g.attr['locus']
for g in combined_gtf:
g.attr['oLocus'] = g.attr['locus']
g.attr['locus'] = namemap[g.attr['locus']]
print g
def main(args):
# Load the internal GTF
combined_gtf = [GTFLine(l) for l in tab_line_gen(args.internalGTF)]
combined_gtf = [g for g in combined_gtf if not g.source=='span_internal']
# Load the left GTF
for l in tab_line_gen(args.ltrGTF):
l_b = GTFLine(l[10:])
l_b.attr['locus'] = GTFLine(l[:9]).attr['locus']
combined_gtf.append(l_b)
byloc = defaultdict(list)
for g in combined_gtf:
byloc[g.attr['locus']].append(g)
#for locid,ilocus in itertools.groupby(combined_gtf, key=lambda x:x.attr['locus']):
for locid,locus in byloc.iteritems():
locus = utils.remove_dups(locus)
locus = utils.adjust_overlaps(locus)
category = locus_category(locus)
for a in locus:
a.source = category
spanning = utils.create_spanning(locus)
spanning.attr = {'category': category,
'locus': locid }
print >>args.outfile, '### %s ###' % locid
print >>args.outfile, spanning
print >>args.outfile, '\n'.join(str(_) for _ in sorted(locus,key=lambda x:x.start))
def main(args):
# Load the internal GTF
combined_gtf = [GTFLine(l) for l in utils.tab_line_gen(args.internalGTF)]
combined_gtf = [g for g in combined_gtf if not g.feature.startswith('span')]
# Load the LTR GTF
for l in utils.tab_line_gen(args.ltrGTF):
l_b = GTFLine(l[-10:])
l_b.attr['locus'] = GTFLine(l[:9]).attr['locus']
combined_gtf.append(l_b)
model_lengths = utils.guess_rmsk_model_lengths(combined_gtf)
# Organize by locus
byloc = defaultdict(list)
for g in combined_gtf:
byloc[g.attr['locus']].append(g)
for locid,locus in byloc.iteritems():
# Remove duplicate annotations
locus = utils.remove_dups(locus)
# Adjust overlaps
locus = utils.adjust_overlaps(locus)
# Determine category
category = locus_category(locus)
# Add information to all annotations
strand = set([a.strand for a in locus])
if len(strand) == 1 and '-' in locus:
locus.sort(key=lambda x:x.end, reverse=True)
else:
locus.sort(key=lambda x:x.start)
for i,a in enumerate(locus):
a.source = category
a.attr['exon_number'] = i+1
# Create spanning annotation
spanning = utils.create_spanning(locus)
# Calculate model coverage and percent
internal_model = get_internal_model(locus)
model_cov = calculate_internal_coverage(locus)
model_pct = min(100, (float(model_cov) / model_lengths[internal_model])*100)
spanning.attr = {'locus': locid ,
'category': category,
'model_cov': model_cov,
'model_pct': '%.1f' % model_pct,
'exons':len(locus)
}
print >>args.outfile, '### %s ###' % locid
print >>args.outfile, spanning
print >>args.outfile, '\n'.join(str(_) for _ in sorted(locus,key=lambda x:x.start))
def main(parser):
args = parser.parse_args()
rows = []
base_columns = [
'chrom', 'source', 'feature', 'start', 'end', 'score', 'strand',
'frame'
]
attr_columns = set()
# Parse rows
gtflines = utils.tab_line_gen(args.infile)
for l in utils.sort_gtf(gtflines):
rowd = dict(zip(base_columns, l[:8]))
for k, v in re.findall('(\S+)\s+"([\s\S]+?)";', l[8]):
attr_columns.add(k)
rowd[k] = v
rows.append(rowd)
# Set column headers
columns = base_columns + list(attr_columns)
if args.keycol in columns:
columns.remove(args.keycol)
columns = [args.keycol] + columns
# Print the table
print >> args.outfile, '\t'.join(columns)
for rowd in rows:
print >> args.outfile, '\t'.join(
[rowd[c] if c in rowd else '' for c in columns])
def main(args):
### Read the GTF file ################################################################
gtf = [GTFLine(l) for l in utils.tab_line_gen(args.infile)]
bychrom = defaultdict(lambda:{'+':list(), '-':list()})
for g in gtf:
bychrom[g.chrom][g.strand].append(g)
merged_hits = []
for cchrom, strands in bychrom.iteritems():
# Plus strand
if len(strands['+']):
strands['+'].sort(key=lambda x:x.start)
cur = [ strands['+'][0] ]
for g1 in strands['+'][1:]:
g0 = cur[-1]
# Genomic distance between hits
gdist = g1.start - g0.end
if gdist <= args.shortdist:
domerge = True
else:
domerge = g0.attr['repLeft'] < g1.attr['repLeft']
domerge &= gdist < args.longdist
if domerge:
cur.append(g1)
else:
merged_hits.append(cur)
cur = [ g1 ]
merged_hits.append(cur)
# Minus strand
if len(strands['-']):
strands['-'].sort(key=lambda x:x.end, reverse=True)
cur = [ strands['-'][0] ]
for g1 in strands['-'][1:]:
g0 = cur[-1]
# Genomic distance between hits
gdist = g0.start - g1.end
if gdist <= args.shortdist:
domerge = True
else:
domerge = g0.attr['repStart'] < g1.attr['repStart']
domerge &= gdist < args.longdist
if domerge:
cur.append(g1)
else:
merged_hits.append(cur)
cur = [ g1 ]
merged_hits.append(cur)
for i,cur in enumerate(merged_hits):
locid = '%s_%04d' % (args.prefix, i+1)
spanning = utils.create_spanning(cur)
spanning.attr['locus'] = locid
for g in cur:
g.attr['locus'] = locid
print >>args.outfile, '### %s ###' % locid
print >>args.outfile, spanning
print >>args.outfile, '\n'.join(str(_) for _ in sorted(cur,key=lambda x:x.start))
def main(args):
# Load GTF file
gtf = utils.tab_line_gen(args.infile)
# Skip lines not being merged
for g in gtf:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";',g[8]))
if 'name' in attrd and attrd['name'] == args.name:
break
else:
print >>args.outfile, '\t'.join(g)
# Get all lines for locus to be split
mergelines = [g]
sublines = []
for g in gtf:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";',g[8]))
if g[1]=='merged' and attrd['name'] == args.name:
mergelines.append(g)
elif 'gene_id' in attrd and attrd['gene_id'] == args.name:
sublines.append(g)
else:
break
# Set the new category and names
if args.category:
category1, category2 = args.category.split(',')
else:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";',g[8]))
category1 = attrd['category']
category2 = attrd['category']
if args.newname:
newname1, newname2 = args.newname.split(',')
else:
newname1 = '%s.1' % args.name
newname2 = '%s.2' % args.name
# Print out the edited lines
sub1 = sublines[:args.split]
print >>args.outfile, '\t'.join(make_mergeline(sub1, newname1, category1))
for l in sub1:
l[1] = category1
l[8] = re.sub('gene_id "\S+";', 'gene_id "%s";' % newname1, l[8])
l[8] = re.sub('transcript_id "\S+";', 'transcript_id "%s";' % newname1, l[8])
print >>args.outfile, '\t'.join(l)
sub2 = sublines[args.split:]
print >>args.outfile, '\t'.join(make_mergeline(sub2, newname2, category2))
for l in sub2:
l[1] = category2
l[8] = re.sub('gene_id "\S+";', 'gene_id "%s";' % newname2, l[8])
l[8] = re.sub('transcript_id "\S+";', 'transcript_id "%s";' % newname2, l[8])
print >>args.outfile, '\t'.join(l)
# Resume printing the file
print >>args.outfile, '\t'.join(g)
for g in gtf:
print >>args.outfile, '\t'.join(g)
def main(args):
if args.chroms:
chroms = [l.strip('\n').split('\t')[0] for l in args.chroms]
else:
chroms = None
for l in utils.sort_gtf(utils.tab_line_gen(args.infile), chroms):
print >>args.outfile, '\t'.join(l)
def main(args):
gtf = [GTFLine(l).asdict() for l in utils.tab_line_gen(args.infile)]
allkeys = set(chain.from_iterable(d.keys() for d in gtf))
columns = GTFLine.GTFCOLS + GTFLine.ATTRORDER
columns += [k for k in sorted(allkeys) if k not in columns]
print >>args.outfile, '\t'.join(columns)
for d in gtf:
print >>args.outfile, '\t'.join(str(d[c]) if c in d else '' for c in columns)
def main(args):
names = args.names.split(',')
category = args.category
gtf = utils.tab_line_gen(args.infile)
# Skip lines not being merged
for g in gtf:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";', g[8]))
if 'name' in attrd and attrd['name'] in names:
break
else:
print >> args.outfile, '\t'.join(g)
mergelines = [g]
sublines = []
for g in gtf:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";', g[8]))
if g[1] == 'merged' and attrd['name'] in names:
mergelines.append(g)
elif 'gene_id' in attrd and attrd['gene_id'] in names:
sublines.append(g)
else:
break
# Merge the merge lines
new_merge = mergelines[0][:]
nm_spos = min(int(m[3]) for m in mergelines)
nm_epos = max(int(m[4]) for m in mergelines)
nm_strand = set(m[6] for m in mergelines)
all_attrd = [
dict(re.findall('(\S+)\s+"([\s\S]+?)";', m[8])) for m in mergelines
]
nm_name = all_attrd[0]['name']
nm_category = category if category is not None else all_attrd[0]['category']
nm_nfeats = sum(int(d['nfeats']) for d in all_attrd)
nm_length = (nm_epos - nm_spos)
nm_cov = sum(int(d['cov']) for d in all_attrd)
new_merge[3] = str(nm_spos)
new_merge[4] = str(nm_epos)
new_merge[6] = nm_strand.pop() if len(nm_strand) == 1 else '.'
new_merge[
8] = 'name "%s"; category "%s"; nfeats "%d"; length "%d"; cov "%d";' % (
nm_name, nm_category, nm_nfeats, nm_length, nm_cov)
print >> args.outfile, '\t'.join(new_merge)
for l in sublines:
l[1] = category if category is not None else all_attrd[0]['category']
l[8] = re.sub('gene_id "\S+";', 'gene_id "%s";' % nm_name, l[8])
l[8] = re.sub('transcript_id "\S+";', 'transcript_id "%s";' % nm_name,
l[8])
print >> args.outfile, '\t'.join(l)
# Resume printing the file
print >> args.outfile, '\t'.join(g)
for g in gtf:
print >> args.outfile, '\t'.join(g)
def main(parser):
args = parser.parse_args()
lines = utils.tab_line_gen(args.infile)
clustered = utils.cluster_gtf(lines)
reptypes = utils.by_attribute(clustered, 'repType')
catcount = Counter()
newlines = []
for cnum, c in clustered.iteritems():
c.sort(key=lambda x: int(x[3]))
cluster_id = '%s_%04d' % (args.prefix, int(cnum))
# Categorize cluster according to repeat types and orientation
if reptypes[cnum] == ['ltr', 'internal', 'ltr']:
category = 'prototype'
elif reptypes[cnum] == ['ltr', 'internal'
] or reptypes[cnum] == ['internal', 'ltr']:
category = 'oneside'
elif reptypes[cnum] == ['internal']:
category = 'soloint'
elif reptypes[cnum] == ['ltr']:
category = 'sololtr'
else:
category = 'unusual'
catcount[category] += 1
# Create the parent (merged) annotation
pstart = min(int(l[3]) for l in c)
pend = max(int(l[4]) for l in c)
strands = set(l[6] for l in c)
if len(strands) == 1: pstrand = strands.pop()
else: pstrand = '.' # Strand is ambiguous
pcov = utils.covered_len(c)
pattr = 'name "%s"; category "%s"; nfeats "%d"; length "%d"; cov "%d";' % (
cluster_id, category, len(c), (pend - pstart), pcov)
pline = [
c[0][0], 'merged', 'gene',
str(pstart),
str(pend), '.', pstrand, '.', pattr
]
newlines.append(pline)
for l in c:
l[1] = category
attr = dict(re.findall('(\S+)\s+"([\s\S]+?)";', l[8]))
if 'gene_id' in attr: del attr['gene_id']
if 'transcript_id' in attr: del attr['transcript_id']
l[8] = 'gene_id "%s"; transcript_id "%s"; ' % (cluster_id,
cluster_id)
l[8] = l[8] + ' '.join('%s "%s";' % (k, v)
for k, v in attr.iteritems())
newlines.append(l[:-1])
for l in utils.sort_gtf(newlines):
print >> args.outfile, '\t'.join(l)
for cat in ['prototype', 'oneside', 'soloint', 'sololtr', 'unusual']:
print >> sys.stderr, '%s: %d' % (cat, catcount[cat])
def main(args):
ltrtypes = defaultdict(list)
gtf = utils.tab_line_gen(args.gtf)
for g in gtf:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";', g[8]))
if attrd['repType'] == 'ltr':
ltrtypes[attrd['locus']].append(attrd['repName'])
titer = utils.tab_line_gen(args.infile)
header = titer.next()
print >> args.outfile, '\t'.join(header + ['subfamily'])
for row in titer:
if row[0] in ltrtypes:
subfam = ','.join(sorted(set(ltrtypes[row[0]])))
else:
subfam = ''
print >> sys.stdout, '\t'.join(row + [subfam])
def main(args):
ltrtypes = defaultdict(list)
gtf = utils.tab_line_gen(args.gtf)
for g in gtf:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";',g[8]))
if attrd['repType']=='ltr':
ltrtypes[attrd['locus']].append(attrd['repName'])
titer = utils.tab_line_gen(args.infile)
header = titer.next()
print >>args.outfile, '\t'.join(header + ['subfamily'])
for row in titer:
if row[0] in ltrtypes:
subfam = ','.join(sorted(set(ltrtypes[row[0]])))
else:
subfam = ''
print >>sys.stdout, '\t'.join(row + [subfam])
def main(args):
# Filehandle for rejected loci
if args.reject_gtf is None:
import os
args.reject_gtf = open(os.devnull,'w')
# Filtering parameters
min_internal_pct = args.min_internal_pct * 100
min_internal_bases = args.min_internal_bases
# Load the internal GTF
combined_gtf = [GTFLine(l) for l in utils.tab_line_gen(args.infile)]
model_lengths = utils.guess_rmsk_model_lengths(combined_gtf)
loccounts = Counter()
byloc = defaultdict(list)
for g in combined_gtf:
byloc[g.attr['locus']].append(g)
if min_internal_pct > 0:
print >>sys.stderr, "Removing loci matching less than %d percent of internal model..." % int(min_internal_pct)
if min_internal_bases > 0:
print >>sys.stderr, "Removing loci matching less than %d internal bases..." % min_internal_bases
rejectflag = False
for locid,locus in byloc.iteritems():
spn = utils.get_span(locus)
locus = [a for a in locus if a != spn] # not a.feature.startswith('span')]
category = spn.attr['category']
model_pct = spn.attr['model_pct']
model_cov = spn.attr['model_cov']
if model_pct >= min_internal_pct and model_cov >= min_internal_bases:
loccounts[category] += 1
outh = args.outfile
else:
if not rejectflag:
print >>sys.stderr, 'Removed loci:'
print >>sys.stderr, '%-18s%-6s%-6s%s' % ('locus','bp','pct','category')
rejectflag = True
loccounts['rejected'] += 1
print >>sys.stderr, '%-18s%-6d%-6.1f%s' % (locid, model_cov, model_pct, category)
outh = args.reject_gtf
print >>outh, '### %s ###' % locid
print >>outh, spn
print >>outh, '\n'.join(str(_) for _ in sorted(locus,key=lambda x:x.start))
if not rejectflag:
print >>sys.stderr, 'All passed filter.'
print >>sys.stderr, 'Summary:'
for cat in ['internal','prototype','oneside','unusual','rejected']:
print >>sys.stderr, '%s%d' % (cat.ljust(20), loccounts[cat])
def main(args):
names = args.names.split(',')
category = args.category
gtf = utils.tab_line_gen(args.infile)
# Skip lines not being merged
for g in gtf:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";',g[8]))
if 'name' in attrd and attrd['name'] in names:
break
else:
print >>args.outfile, '\t'.join(g)
mergelines = [g]
sublines = []
for g in gtf:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";',g[8]))
if g[1]=='merged' and attrd['name'] in names:
mergelines.append(g)
elif 'gene_id' in attrd and attrd['gene_id'] in names:
sublines.append(g)
else:
break
# Merge the merge lines
new_merge = mergelines[0][:]
nm_spos = min(int(m[3]) for m in mergelines)
nm_epos = max(int(m[4]) for m in mergelines)
nm_strand = set(m[6] for m in mergelines)
all_attrd = [dict(re.findall('(\S+)\s+"([\s\S]+?)";', m[8])) for m in mergelines]
nm_name = all_attrd[0]['name']
nm_category = category if category is not None else all_attrd[0]['category']
nm_nfeats = sum(int(d['nfeats']) for d in all_attrd)
nm_length = (nm_epos - nm_spos)
nm_cov = sum(int(d['cov']) for d in all_attrd)
new_merge[3] = str(nm_spos)
new_merge[4] = str(nm_epos)
new_merge[6] = nm_strand.pop() if len(nm_strand) == 1 else '.'
new_merge[8] = 'name "%s"; category "%s"; nfeats "%d"; length "%d"; cov "%d";' % (nm_name, nm_category, nm_nfeats, nm_length, nm_cov)
print >>args.outfile, '\t'.join(new_merge)
for l in sublines:
l[1] = category if category is not None else all_attrd[0]['category']
l[8] = re.sub('gene_id "\S+";', 'gene_id "%s";' % nm_name , l[8])
l[8] = re.sub('transcript_id "\S+";', 'transcript_id "%s";' % nm_name , l[8])
print >>args.outfile, '\t'.join(l)
# Resume printing the file
print >>args.outfile, '\t'.join(g)
for g in gtf:
print >>args.outfile, '\t'.join(g)
def main(parser):
args = parser.parse_args()
lines = utils.tab_line_gen(args.infile)
clustered = utils.cluster_gtf(lines)
reptypes = utils.by_attribute(clustered, 'repType')
catcount = Counter()
newlines = []
for cnum,c in clustered.iteritems():
c.sort(key=lambda x:int(x[3]))
cluster_id = '%s_%04d' % (args.prefix,int(cnum))
# Categorize cluster according to repeat types and orientation
if reptypes[cnum] == ['ltr','internal','ltr']:
category = 'prototype'
elif reptypes[cnum] == ['ltr','internal'] or reptypes[cnum] == ['internal','ltr']:
category = 'oneside'
elif reptypes[cnum] == ['internal']:
category = 'soloint'
elif reptypes[cnum] == ['ltr']:
category = 'sololtr'
else:
category = 'unusual'
catcount[category] += 1
# Create the parent (merged) annotation
pstart = min(int(l[3]) for l in c)
pend = max(int(l[4]) for l in c)
strands = set(l[6] for l in c)
if len(strands)==1: pstrand = strands.pop()
else: pstrand = '.' # Strand is ambiguous
pcov = utils.covered_len(c)
pattr = 'name "%s"; category "%s"; nfeats "%d"; length "%d"; cov "%d";' % (cluster_id, category, len(c), (pend-pstart), pcov)
pline = [c[0][0], 'merged', 'gene', str(pstart), str(pend), '.', pstrand, '.', pattr]
newlines.append(pline)
for l in c:
l[1] = category
attr = dict(re.findall('(\S+)\s+"([\s\S]+?)";',l[8]))
if 'gene_id' in attr: del attr['gene_id']
if 'transcript_id' in attr: del attr['transcript_id']
l[8] = 'gene_id "%s"; transcript_id "%s"; ' % (cluster_id,cluster_id)
l[8] = l[8] + ' '.join('%s "%s";' % (k,v) for k,v in attr.iteritems())
newlines.append(l[:-1])
for l in utils.sort_gtf(newlines):
print >>args.outfile, '\t'.join(l)
for cat in ['prototype','oneside','soloint','sololtr','unusual']:
print >>sys.stderr, '%s: %d' % (cat, catcount[cat])
def main(args):
combined_gtf = [GTFLine(l) for l in utils.tab_line_gen(args.infile)]
# Find overlaps within the span features
overlap_groups = utils.find_overlaps([g for g in combined_gtf if g.feature.startswith('span')])
overlap_groups = {k:v for k,v in overlap_groups.iteritems() if len(v) > 1}
print >>sys.stderr, "Found %d groups with conflict." % len(overlap_groups)
# Resolve commands
if args.resolve_file is not None:
resolve_cmds = json.load(args.resolve_file)
else:
if args.resolve is not None:
# Resolve commands were provided as command-line argument
resolve_cmds = args.resolve
else:
# Prompt user to enter resolve commands
resolve_cmds = {}
for groupid in sorted(overlap_groups.keys(), key=lambda x:int(x)):
ogroup = overlap_groups[groupid]
print >>sys.stderr, utils.groupstr(groupid, ogroup)
concmd = utils.prompt_cmd()
resolve_cmds[groupid] = concmd
print >>sys.stderr, 'Commands for resolving conflicts (JSON):\n'
print >>sys.stderr, json.dumps(resolve_cmds)
# Resolve the conflicts
byloc = defaultdict(list)
for g in combined_gtf:
byloc[g.attr['locus']].append(g)
for groupid, ogroup in overlap_groups.iteritems():
print >>sys.stderr, utils.groupstr(groupid, ogroup)
locids = [a.attr['locus'] for a in ogroup]
# Temporarily remove the loci
fulllocs = {}
for locid in locids:
print >>sys.stderr, '\tRemoving %s' % locid
fulllocs[locid] = byloc.pop(locid)
assert groupid in resolve_cmds
newlocs = resolve(resolve_cmds[groupid], ogroup, fulllocs)
for newlocid, newlocus in newlocs.iteritems():
print >>sys.stderr, '\tInserting %s' % newlocid
# print >>sys.stderr, '\n'.join(str(_) for _ in newlocus)
byloc.update(newlocs)
for locid,locus in byloc.iteritems():
print >>args.outfile, '### %s ###' % locid
print >>args.outfile, '\n'.join(str(_) for _ in sorted(locus,key=lambda x:x.start))
def main(args):
discard = set()
discard_fh = open(args.discard, 'w')
lines = utils.tab_line_gen(args.infile)
for l in lines:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";',l[8]))
if l[1] == 'merged':
cov = int(attrd['cov'])
if cov < args.threshold:
discard.add(attrd['name'])
print >>discard_fh, '\t'.join(l)
else:
print >>args.outfile, '\t'.join(l)
else:
if attrd['gene_id'] in discard:
print >>discard_fh, '\t'.join(l)
else:
print >>args.outfile, '\t'.join(l)
def main(args):
discard = set()
discard_fh = open(args.discard, 'w')
lines = utils.tab_line_gen(args.infile)
for l in lines:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";', l[8]))
if l[1] == 'merged':
cov = int(attrd['cov'])
if cov < args.threshold:
discard.add(attrd['name'])
print >> discard_fh, '\t'.join(l)
else:
print >> args.outfile, '\t'.join(l)
else:
if attrd['gene_id'] in discard:
print >> discard_fh, '\t'.join(l)
else:
print >> args.outfile, '\t'.join(l)
def main(args):
### Read the GTF file ################################################################
gtf = [GTFLine(l) for l in utils.tab_line_gen(args.infile)]
### Correct model coordinates ########################################################
# The repStart, repEnd, and repLeft attributes downloaded from the UCSC rmsk database
# does not always give the same model length. Here we guess what the correct model
# length is then correct each record
mlen = utils.guess_rmsk_model_lengths(gtf)
print >>sys.stderr, 'Model lengths:'
print >>sys.stderr, '\n'.join('%s%d' % (k.ljust(16), mlen[k]) for k in sorted(mlen.keys()))
correct_rmsk_model_coordinates(gtf,mlen)
# Check that model coordinates are correct
for g in gtf:
if g.strand == '+':
trueend = mlen[g.attr['repName']] + g.attr['repLeft']
else:
trueend = mlen[g.attr['repName']] + g.attr['repStart']
assert trueend == g.attr['repEnd']
print >>args.outfile, g
def main(parser):
args = parser.parse_args()
lines = utils.tab_line_gen(args.infile)
for l in utils.sort_gtf(lines):
print >>args.outfile, '\t'.join(l)
def main(args):
### Read the GTF file ################################################################
print >> sys.stderr, 'Loading GTF: %s' % args.internal_file
gtf = [
GTFLine(l) for l in utils.tab_line_gen(open(args.internal_file, 'rU'))
]
### Get model lengths
# mlen = calculate_model_lengths(gtf)
# print mlen
mlen = calculate_model_lengths2(gtf)
print >> sys.stderr, 'Model lengths: %s' % mlen
### Correct the model coordinates ####################################################
correct_model_coordinates(gtf, mlen)
for g in gtf:
if g.strand == '+':
trueend = mlen[g.attr['repName']] + g.attr['repLeft']
else:
trueend = mlen[g.attr['repName']] + g.attr['repStart']
assert trueend == g.attr['repEnd']
### Organize hits by chromosome ######################################################
bychrom = defaultdict(list)
for g in gtf:
bychrom[g.chrom].append(g)
### List of HERV loci ################################################################
print >> sys.stderr, 'Assembling HERV loci'
all_locs = []
### Create HERV loci for plus strand #################################################
for chrom in utils.CHROMNAMES:
if chrom in bychrom:
plus = [h for h in bychrom[chrom] if h.strand == '+']
if not plus: continue
plus.sort(key=lambda x: x.start)
cur = HERVLocus(id='%s_%04d' % (args.prefix, len(all_locs) + 1))
cur.internal.append(plus[0])
for p1 in plus[1:]:
p0 = cur.internal[-1]
# Genomic distance between hits
gdist = p1.start - p0.end
# Determine whether p1 is in sequence with locus
if gdist <= 10: ## Overlapping (or nearly) in genome
insequence = True
else:
## Hits are in sequence and genomic distance is not extreme
insequence = p0.attr['repLeft'] < p1.attr['repLeft']
insequence &= gdist < args.longdist
if insequence:
cur.internal.append(p1)
else:
all_locs.append(cur)
cur = HERVLocus(id='%s_%04d' %
(args.prefix, len(all_locs) + 1))
cur.internal.append(p1)
all_locs.append(cur)
### Create HERV loci for minus strand ################################################
for chrom in utils.CHROMNAMES:
if chrom in bychrom:
minus = [h for h in bychrom[chrom] if h.strand == '-']
if not minus: continue
minus.sort(key=lambda x: x.end,
reverse=True) # Sort in reverse order
cur = HERVLocus(id='%s_%04d' % (args.prefix, len(all_locs) + 1))
cur.internal.append(minus[0])
for p1 in minus[1:]:
p0 = cur.internal[-1]
# Genomic distance between hits
gdist = p0.start - p1.end
# Determine whether p1 is in sequence with locus
if gdist <= 10: ## Overlapping (or nearly) in genome
insequence = True
else:
## Hits are in sequence and genomic distance is not extreme
insequence = p0.attr['repStart'] < p1.attr['repStart']
insequence &= gdist < args.longdist
if insequence:
cur.internal.append(p1)
else:
all_locs.append(cur)
cur = HERVLocus(id='%s_%04d' %
(args.prefix, len(all_locs) + 1))
cur.internal.append(p1)
all_locs.append(cur)
### Add LTRs to HERV loci ############################################################
print >> sys.stderr, 'Finding flanking LTRs'
for loc in all_locs:
loc.find_ltr(args.ltr_files, args.flank)
loc.adjust_overlaps()
print >> sys.stderr, "Initial counts:"
print >> sys.stderr, '\n'.join('%s%d' % (cat.ljust(20, ' '), count)
for cat, count in Counter(
c.category()
for c in all_locs).most_common())
### Filtering ########################################################################
reject = set()
if args.minpct > 0 or args.mincov > 0:
print >> sys.stderr, "Removing loci with less than %d percent or %dbp model coverage" % (
int(args.minpct * 100), args.mincov)
for loc in all_locs:
if loc.model_cov() < (mlen[loc.internal_name()] * args.minpct
) or loc.model_cov() < args.mincov:
print >> sys.stderr, '%s\t%d\t%s' % (loc.id, loc.model_cov(),
loc.category())
reject.add(loc)
for rloc in reject:
all_locs.remove(rloc)
print >> sys.stderr, "After filtering:"
print >> sys.stderr, '\n'.join('%s%d' % (cat.ljust(20, ' '), count)
for cat, count in Counter(
c.category()
for c in all_locs).most_common())
print >> sys.stderr, '%s%d' % ('Rejected'.ljust(20, ' '), len(reject))
### Deal with overlapping loci #######################################################
# Create GTF with all_locs
with open('tmp.gtf', 'w') as outh:
for g in utils.sort_gtf(loc.span_gtf() for loc in all_locs):
print >> outh, '\t'.join(g)
# Cluster overlapping and bookended using bedtools
p1 = Popen('bedtools cluster -i tmp.gtf',
shell=True,
stdout=PIPE,
stderr=PIPE)
out, err = p1.communicate()
os.remove('tmp.gtf')
# Parse bedtools output
overlap_groups = defaultdict(list)
for ll in out.strip('\n').split('\n'):
f = ll.split('\t')
overlap_groups[f[-1]].append(GTFLine(f[:9]))
# Remove clusters with one
for k in overlap_groups.keys():
if len(overlap_groups[k]) == 1:
del overlap_groups[k]
print >> sys.stderr, "%d overlap groups" % len(overlap_groups)
if args.igv_preview and len(overlap_groups) > 0:
print >> sys.stderr, "Loading IGV"
# Create file for IGV viewing
with open('tmp.gtf', 'w') as outh:
liter = utils.sort_gtf(
chain.from_iterable(loc.each_gtf() for loc in all_locs))
print >> outh, '\n'.join('\t'.join(_) for _ in liter)
igv = IGV()
igv.new()
igv.genome('hg19')
igv.load(
os.path.join(os.getcwd(), '../other_sources/rmsk_LTR.hg19.gtf'))
igv.load(os.path.join(os.getcwd(), 'tmp.gtf'))
tandem = []
for k in sorted(overlap_groups.keys(), key=lambda x: int(x)):
ogroup = overlap_groups[k]
if args.igv_preview:
locus_str = '%s:%s-%s' % (ogroup[0].chrom,
min(gl.start for gl in ogroup) - 5000,
max(gl.end for gl in ogroup) + 5000)
igv.goto(locus_str)
igv.expand()
# Get locus for each member of overlap group
og_locus = {}
for o in ogroup:
tmp = [c for c in all_locs if c.id == o.attr['name']]
assert len(tmp) == 1
og_locus[o.attr['name']] = tmp[0]
# Print out the model coverage
for n, loc in og_locus.iteritems():
print >> sys.stderr, '%s\t%d\t%s' % (n, loc.model_cov(),
loc.category())
# Parse user input
z = raw_input('Action to take: ').strip()
if z == '': continue
inputcmd = z.strip().split(' ')
if inputcmd[0] == 'REJECT':
if len(inputcmd) == 1:
# Only max will be kept
st = sorted([loc for n, loc in og_locus.iteritems()],
key=lambda x: x.model_cov(),
reverse=True)[1:]
loc_ids = [_.id for _ in st]
elif len(inputcmd) == 2:
loc_ids = inputcmd[1].split(',')
else:
assert False
for loc_id in loc_ids:
reject.add(og_locus[loc_id])
elif inputcmd[0] == 'TANDEM':
if len(inputcmd) == 1:
assert len(og_locus) == 2, 'More than 2 loci are present'
tandem.append([loc for n, loc in og_locus.iteritems()])
elif len(inputcmd) == 2:
loc_ids = inputcmd[1].split('+')
tandem.append([og_locus[loc_id] for loc_id in loc_ids])
else:
assert False
elif inputcmd[0] == 'DIFF':
n1, n2 = inputcmd[1].split('-')
g1 = og_locus[n1]
g2 = og_locus[n2]
if g1.span()[0] < g2.span()[1]:
g1.shorten(g2.span()[1] + 20, g1.span()[1])
elif g1.span()[1] < g2.span()[0]:
g1.shorten(g1.span()[0], g2.span()[0] - 20)
else:
print "no overlap!"
print g1
elif inputcmd[0] == 'IGNORE':
continue
else:
assert False, 'Unknown command: "%s"' % inputcmd[0]
# Remove rejected annotations
for rloc in reject:
if rloc in all_locs:
all_locs.remove(rloc)
# Create the tandem annotations
for tgroup in tandem:
tandem_loc = HERVLocus(id=tgroup[0].id)
tandem_loc.internal = list(
chain.from_iterable(loc.internal for loc in tgroup))
if tandem_loc.strand() == '+':
tandem_loc.internal.sort(key=lambda x: x.start)
else:
tandem_loc.internal.sort(key=lambda x: x.end, reverse=True)
tandem_loc.find_ltr(args.ltr_files, 1000)
tandem_loc.adjust_overlaps()
tandem_loc.is_tandem = True
all_locs.append(tandem_loc)
# Remove from original
for rloc in tgroup:
all_locs.remove(rloc)
print >> sys.stderr, "After overlap removal:"
print >> sys.stderr, '\n'.join('%s%d' % (cat.ljust(20, ' '), count)
for cat, count in Counter(
c.category()
for c in all_locs).most_common())
print >> sys.stderr, '%s%d' % ('Rejected'.ljust(20, ' '), len(reject))
if args.igv_preview and len(overlap_groups) > 0: os.remove('tmp.gtf')
### Sort loci ########################################################################
bychrom = defaultdict(list)
for loc in all_locs:
bychrom[loc.chrom()].append(loc)
final_locs = []
for chrom in utils.CHROMNAMES:
if chrom in bychrom:
for loc in sorted(bychrom[chrom], key=lambda x: x.span()[0]):
final_locs.append(loc)
for i, loc in enumerate(final_locs):
loc.id = '%s_%04d' % (args.prefix, i + 1)
### Rename loci according to cytoband #################################################
# Create GTF with all_locs
with open('tmp.gtf', 'w') as outh:
for g in utils.sort_gtf(loc.span_gtf() for loc in final_locs):
print >> outh, '\t'.join(g)
p1 = Popen(
'bedtools intersect -wo -a tmp.gtf -b ../other_sources/cytoband.gtf',
shell=True,
stdout=PIPE,
stderr=PIPE)
out, err = p1.communicate()
os.remove('tmp.gtf')
byband = defaultdict(list)
for ll in out.strip('\n').split('\n'):
f = ll.split('\t')
g1 = GTFLine(f[:9])
g2 = GTFLine(f[9:-1])
band = '%s%s' % (g2.chrom.strip('chr'), g2.attr['gene_id'])
byband[band].append(g1)
namemap = {}
for band, glist in byband.iteritems():
if len(glist) == 1:
namemap[glist[0].attr['name']] = '%s_%s' % (args.prefix, band)
else:
glist.sort(key=lambda x: x.start)
for i, gl in enumerate(glist):
namemap[gl.attr['name']] = '%s_%s%s' % (args.prefix, band,
someletters[i])
for loc in final_locs:
loc.locus_name = namemap[loc.id]
### Create annotation files ##########################################################
print >> sys.stderr, "Writing annotation files"
with open('%s.gtf' % args.prefix, 'w') as outh:
liter = utils.sort_gtf(
chain.from_iterable(loc.each_gtf() for loc in final_locs))
print >> outh, '\n'.join('\t'.join(_) for _ in liter)
# for loc in final_locs:
# print >>outh, '\n'.join('\t'.join(g) for g in loc.each_gtf())
with open('%s_reject.gtf' % args.prefix, 'w') as outh:
liter = utils.sort_gtf(
chain.from_iterable(loc.each_gtf() for loc in reject))
print >> outh, '\n'.join('\t'.join(_) for _ in liter)
# for loc in reject:
# print >>outh, '\n'.join('\t'.join(g) for g in loc.each_gtf())
with open('%s_span.gtf' % args.prefix, 'w') as outh:
for g in utils.sort_gtf(loc.span_gtf() for loc in final_locs):
print >> outh, '\t'.join(g)
with open('%s_table.txt' % args.prefix, 'w') as outh:
print >> outh, '\t'.join([
'locus_name', 'id', 'strand', 'chrom', 'start', 'end', 'strand',
'nfeats', 'width', 'model_cov', 'ltr5_model', 'int_model',
'ltr3_model'
])
for loc in final_locs:
mgtf = GTFLine(loc.span_gtf())
row = [
loc.locus_name,
loc.id,
loc.category(),
mgtf.chrom,
mgtf.start,
mgtf.end,
mgtf.strand,
mgtf.attr['nfeats'],
loc.width(),
loc.model_cov(),
loc.ltr_up_name(),
loc.internal_name(),
loc.ltr_down_name(),
]
print >> outh, '\t'.join(str(_) for _ in row)
### Extract sequences ################################################################
if args.get_sequences:
print >> sys.stderr, "Extracting sequences"
genome_fasta = args.genome_fasta # '/Users/bendall/Projects/References/Homo_sapiens/UCSC/hg19/Sequence/WholeGenomeFasta/genome.fa'
genome = dict((s.id, s) for s in SeqIO.parse(genome_fasta, 'fasta'))
with open('%s.full.fasta' % args.prefix, 'w') as outh:
for loc in final_locs:
gcoord = '%s:%d-%d(%s)' % (loc.chrom(), loc.span()[0],
loc.span()[1], loc.strand())
print >> outh, '>%s|%s|%s' % (loc.locus_name, loc.category(),
gcoord)
print >> outh, str(loc.entire_sequence(genome).seq)
with open('%s.internal.fasta' % args.prefix, 'w') as outh:
for loc in final_locs:
gcoord = '%s:%d-%d(%s)' % (
loc.chrom(), min(p.start for p in loc.internal),
max(p.end for p in loc.internal), loc.strand())
print >> outh, '>%s_int|%s|%s|%s' % (loc.locus_name,
loc.category(), gcoord,
loc.format_print_clust())
print >> outh, str(loc.internal_sequence(genome).seq)
with open('%s.5ltr.fasta' % args.prefix, 'w') as outh:
for loc in final_locs:
ltrseq = loc.ltr_up_sequence(genome)
if ltrseq:
gcoord = '%s:%d-%d(%s)' % (
loc.chrom(), min(p.start for p in loc.ltr_up),
max(p.end for p in loc.ltr_up), loc.strand())
print >> outh, '>%s_5LTR|%s|%s' % (
loc.locus_name, loc.ltr_up_name(), gcoord)
print >> outh, str(ltrseq.seq)
with open('%s.3ltr.fasta' % args.prefix, 'w') as outh:
for loc in final_locs:
ltrseq = loc.ltr_down_sequence(genome)
if ltrseq:
gcoord = '%s:%d-%d(%s)' % (
loc.chrom(), min(p.start for p in loc.ltr_down),
max(p.end for p in loc.ltr_down), loc.strand())
print >> outh, '>%s_3LTR|%s|%s' % (
loc.locus_name, loc.ltr_down_name(), gcoord)
print >> outh, str(ltrseq.seq)
### IGV snapshots ####################################################################
if args.igv_snapshot:
print >> sys.stderr, "Taking IGV snapshots"
igv = IGV()
igv.new()
igv.genome('hg19')
igv.load(
os.path.join(os.getcwd(), '../other_sources/rmsk_LTR.hg19.gtf'))
if os.path.isdir('tmp'):
for compare_gtf in glob('tmp/*.gtf'):
igv.load(os.path.join(os.getcwd(), compare_gtf))
igv.load(os.path.join(os.getcwd(), '%s.gtf' % args.prefix))
igv.load(os.path.join(os.getcwd(), '%s_reject.gtf' % args.prefix))
do_snapshots = True
if do_snapshots:
if not os.path.exists(os.path.join(os.getcwd(), 'snapshots')):
os.mkdir(os.path.join(os.getcwd(), 'snapshots'))
if not os.path.exists(os.path.join(os.getcwd(), 'reject')):
os.mkdir(os.path.join(os.getcwd(), 'reject'))
categories = ['prototype', 'oneside', 'internal']
for cat in categories:
if not os.path.exists(
os.path.join(os.getcwd(), 'snapshots/%s' % cat)):
os.mkdir(os.path.join(os.getcwd(), 'snapshots/%s' % cat))
if not os.path.exists(
os.path.join(os.getcwd(), 'reject/%s' % cat)):
os.mkdir(os.path.join(os.getcwd(), 'reject/%s' % cat))
for loc in final_locs:
rc, lc = loc.span()
locus_str = '%s:%d-%d' % (loc.chrom(), rc - 5000, lc + 5000)
print >> sys.stderr, '%s\t%s\t%s' % (loc.locus_name,
loc.category(), locus_str)
igv.goto(locus_str)
igv.expand()
if do_snapshots:
igv.snapshotDirectory(
os.path.join(os.getcwd(),
'snapshots/%s' % loc.category().strip('*')))
igv.snapshot(filename='%s.png' % loc.locus_name)
for loc in reject:
rc, lc = loc.span()
locus_str = '%s:%d-%d' % (loc.chrom(), rc - 5000, lc + 5000)
print >> sys.stderr, '%s\t%s\t%s' % (loc.id, loc.category(),
locus_str)
igv.goto(locus_str)
igv.expand()
if do_snapshots:
igv.snapshotDirectory(
os.path.join(os.getcwd(),
'reject/%s' % loc.category().strip('*')))
igv.snapshot(filename='%s.png' % loc.id)
def main(parser):
args = parser.parse_args()
lines = utils.tab_line_gen(args.infile)
bystrand = {"+": [], "-": []}
for l in lines:
bystrand[l[6]].append(l)
bystrand["+"] = list(utils.sort_gtf(bystrand["+"]))
bystrand["-"] = list(utils.sort_gtf(bystrand["-"]))
grouped = {"+": [], "-": []}
for strand in ["+", "-"]:
score = None
chrom = None
tmp = []
for l in bystrand[strand]:
if score is not None:
if l[5] != score or l[0] != chrom:
grouped[strand].append(tmp)
tmp = []
tmp.append(l)
score = l[5]
chrom = l[0]
gaplens = []
merged = []
for g in grouped["+"] + grouped["-"]:
if len(g) == 1:
merged.append(g[0])
else:
mygaps = []
s = ""
for i in range(len(g) - 1):
gaplen = int(g[i + 1][3]) - int(g[i][4])
s += "%s:%s-%s(%s)" % (g[i][0], g[i][3], g[i][4], g[i][6])
s += " --- %d --- " % gaplen
mygaps.append(gaplen)
s += "%s:%s-%s(%s)" % (g[-1][0], g[-1][3], g[-1][4], g[-1][6])
if any(g >= QUESTIONABLE for g in mygaps):
continue
else:
gaplens.extend(mygaps)
print >>sys.stderr, s
# spos = min(int(l[3]) for l in g)
# epos = max(int(l[4]) for l in g)
# attrs = [dict(re.findall('(\S+)\s+"([\s\S]+?)";',l[8])) for l in g]
# newline = [g[0][0], 'joined', 'exon', str(spos), str(epos), g[0][5], g[0][6], '.']
# newattr = {'joined': ','.join(a['id'] for a in attrs),
# 'repType': attrs[0]['repType'],
# }
# newline.append(' '.join('%s "%s";' % (k,v) for k,v in newattr.iteritems()))
# merged.append(newline)
if gaplens:
print >>sys.stderr, "min gap length: %d" % min(gaplens)
print >>sys.stderr, "mean gap length: %d" % (float(sum(gaplens)) / len(gaplens))
print >>sys.stderr, "median gap length: %d" % sorted(gaplens)[len(gaplens) / 2]
print >>sys.stderr, "max gap length: %d" % max(gaplens)
else:
print >>sys.stderr, "No gaps found"
print >>args.outfile, "%d" % max(gaplens)
def main(args):
combined_gtf = [GTFLine(l) for l in utils.tab_line_gen(args.infile)]
for g in combined_gtf:
if args.fromAttr in g.attr:
g.attr[args.toAttr] = g.attr[args.fromAttr]
print >>args.outfile, g
def main(args):
# Load GTF file
gtf = utils.tab_line_gen(args.infile)
# Skip lines not being merged
for g in gtf:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";', g[8]))
if 'name' in attrd and attrd['name'] == args.name:
break
else:
print >> args.outfile, '\t'.join(g)
# Get all lines for locus to be split
mergelines = [g]
sublines = []
for g in gtf:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";', g[8]))
if g[1] == 'merged' and attrd['name'] == args.name:
mergelines.append(g)
elif 'gene_id' in attrd and attrd['gene_id'] == args.name:
sublines.append(g)
else:
break
# Set the new category and names
if args.category:
category1, category2 = args.category.split(',')
else:
attrd = dict(re.findall('(\S+)\s+"([\s\S]+?)";', g[8]))
category1 = attrd['category']
category2 = attrd['category']
if args.newname:
newname1, newname2 = args.newname.split(',')
else:
newname1 = '%s.1' % args.name
newname2 = '%s.2' % args.name
# Print out the edited lines
sub1 = sublines[:args.split]
print >> args.outfile, '\t'.join(make_mergeline(sub1, newname1, category1))
for l in sub1:
l[1] = category1
l[8] = re.sub('gene_id "\S+";', 'gene_id "%s";' % newname1, l[8])
l[8] = re.sub('transcript_id "\S+";', 'transcript_id "%s";' % newname1,
l[8])
print >> args.outfile, '\t'.join(l)
sub2 = sublines[args.split:]
print >> args.outfile, '\t'.join(make_mergeline(sub2, newname2, category2))
for l in sub2:
l[1] = category2
l[8] = re.sub('gene_id "\S+";', 'gene_id "%s";' % newname2, l[8])
l[8] = re.sub('transcript_id "\S+";', 'transcript_id "%s";' % newname2,
l[8])
print >> args.outfile, '\t'.join(l)
# Resume printing the file
print >> args.outfile, '\t'.join(g)
for g in gtf:
print >> args.outfile, '\t'.join(g)
#! /usr/bin/env python
import sys
import re
import utils
from collections import defaultdict
cyto = dict([l.strip('\n').split('\t') for l in open('tmp/cyto_name_map.txt','rU')])
lines = list(utils.tab_line_gen(open('filtered.hg19.gtf','rU')))
### Seperate merged and unmerged lines
### Group unmerged lines according to gene
merged = []
unmerged = defaultdict(list)
for l in lines:
attrs = dict(re.findall('(\S+)\s+"([\s\S]+?)";',l[8]))
if l[1]=='merged':
merged.append((attrs['name'],l))
else:
attrs = dict(re.findall('(\S+)\s+"([\s\S]+?)";',l[8]))
unmerged[attrs['gene_id']].append(l)
sdata = defaultdict(dict)
for mname,ml in merged:
attrs = dict(re.findall('(\S+)\s+"([\s\S]+?)";',ml[8]))
sdata[mname]['category'] = attrs['category']
sdata[mname]['band'] = cyto[mname]
sdata[mname]['id'] = mname
sdata[mname]['start'] = int(ml[3])
sdata[mname]['chrom'] = ml[0]
sdata[mname]['alias'] = ''
def main(args):
### Read the GTF file ################################################################
print >>sys.stderr, 'Loading GTF: %s' % args.internal_file
gtf = [GTFLine(l) for l in utils.tab_line_gen(open(args.internal_file,'rU'))]
### Get model lengths
# mlen = calculate_model_lengths(gtf)
# print mlen
mlen = calculate_model_lengths2(gtf)
print >>sys.stderr, 'Model lengths: %s' % mlen
### Correct the model coordinates ####################################################
correct_model_coordinates(gtf,mlen)
for g in gtf:
if g.strand == '+':
trueend = mlen[g.attr['repName']] + g.attr['repLeft']
else:
trueend = mlen[g.attr['repName']] + g.attr['repStart']
assert trueend == g.attr['repEnd']
### Organize hits by chromosome ######################################################
bychrom = defaultdict(list)
for g in gtf:
bychrom[g.chrom].append(g)
### List of HERV loci ################################################################
print >>sys.stderr, 'Assembling HERV loci'
all_locs = []
### Create HERV loci for plus strand #################################################
for chrom in utils.CHROMNAMES:
if chrom in bychrom:
plus = [h for h in bychrom[chrom] if h.strand == '+']
if not plus: continue
plus.sort(key=lambda x: x.start)
cur = HERVLocus(id='%s_%04d' % (args.prefix, len(all_locs)+1))
cur.internal.append(plus[0])
for p1 in plus[1:]:
p0 = cur.internal[-1]
# Genomic distance between hits
gdist = p1.start - p0.end
# Determine whether p1 is in sequence with locus
if gdist <= 10: ## Overlapping (or nearly) in genome
insequence = True
else:
## Hits are in sequence and genomic distance is not extreme
insequence = p0.attr['repLeft'] < p1.attr['repLeft']
insequence &= gdist < args.longdist
if insequence:
cur.internal.append(p1)
else:
all_locs.append(cur)
cur = HERVLocus(id='%s_%04d' % (args.prefix, len(all_locs)+1))
cur.internal.append(p1)
all_locs.append(cur)
### Create HERV loci for minus strand ################################################
for chrom in utils.CHROMNAMES:
if chrom in bychrom:
minus = [h for h in bychrom[chrom] if h.strand == '-']
if not minus: continue
minus.sort(key=lambda x: x.end, reverse=True) # Sort in reverse order
cur = HERVLocus(id='%s_%04d' % (args.prefix, len(all_locs)+1))
cur.internal.append(minus[0])
for p1 in minus[1:]:
p0 = cur.internal[-1]
# Genomic distance between hits
gdist = p0.start - p1.end
# Determine whether p1 is in sequence with locus
if gdist <= 10: ## Overlapping (or nearly) in genome
insequence = True
else:
## Hits are in sequence and genomic distance is not extreme
insequence = p0.attr['repStart'] < p1.attr['repStart']
insequence &= gdist < args.longdist
if insequence:
cur.internal.append(p1)
else:
all_locs.append(cur)
cur = HERVLocus(id='%s_%04d' % (args.prefix, len(all_locs)+1))
cur.internal.append(p1)
all_locs.append(cur)
### Add LTRs to HERV loci ############################################################
print >>sys.stderr, 'Finding flanking LTRs'
for loc in all_locs:
loc.find_ltr(args.ltr_files, args.flank)
loc.adjust_overlaps()
print >>sys.stderr, "Initial counts:"
print >>sys.stderr, '\n'.join('%s%d' % (cat.ljust(20,' '),count) for cat,count in Counter(c.category() for c in all_locs).most_common())
### Filtering ########################################################################
reject = set()
if args.minpct > 0 or args.mincov > 0:
print >>sys.stderr, "Removing loci with less than %d percent or %dbp model coverage" % (int(args.minpct*100), args.mincov)
for loc in all_locs:
if loc.model_cov() < (mlen[loc.internal_name()] * args.minpct) or loc.model_cov() < args.mincov:
print >>sys.stderr, '%s\t%d\t%s' % (loc.id, loc.model_cov(), loc.category())
reject.add(loc)
for rloc in reject:
all_locs.remove(rloc)
print >>sys.stderr, "After filtering:"
print >>sys.stderr, '\n'.join('%s%d' % (cat.ljust(20,' '),count) for cat,count in Counter(c.category() for c in all_locs).most_common())
print >>sys.stderr, '%s%d' % ('Rejected'.ljust(20,' '), len(reject))
### Deal with overlapping loci #######################################################
# Create GTF with all_locs
with open('tmp.gtf','w') as outh:
for g in utils.sort_gtf(loc.span_gtf() for loc in all_locs):
print >>outh, '\t'.join(g)
# Cluster overlapping and bookended using bedtools
p1 = Popen('bedtools cluster -i tmp.gtf', shell=True, stdout=PIPE, stderr=PIPE)
out,err = p1.communicate()
os.remove('tmp.gtf')
# Parse bedtools output
overlap_groups = defaultdict(list)
for ll in out.strip('\n').split('\n'):
f = ll.split('\t')
overlap_groups[f[-1]].append(GTFLine(f[:9]))
# Remove clusters with one
for k in overlap_groups.keys():
if len(overlap_groups[k]) == 1:
del overlap_groups[k]
print >>sys.stderr, "%d overlap groups" % len(overlap_groups)
if args.igv_preview and len(overlap_groups)>0:
print >>sys.stderr, "Loading IGV"
# Create file for IGV viewing
with open('tmp.gtf','w') as outh:
liter = utils.sort_gtf(chain.from_iterable(loc.each_gtf() for loc in all_locs))
print >>outh, '\n'.join('\t'.join(_) for _ in liter)
igv = IGV()
igv.new()
igv.genome('hg19')
igv.load(os.path.join(os.getcwd(),'../other_sources/rmsk_LTR.hg19.gtf'))
igv.load(os.path.join(os.getcwd(),'tmp.gtf'))
tandem = []
for k in sorted(overlap_groups.keys(), key=lambda x:int(x)):
ogroup = overlap_groups[k]
if args.igv_preview:
locus_str = '%s:%s-%s' % (ogroup[0].chrom, min(gl.start for gl in ogroup)-5000, max(gl.end for gl in ogroup)+5000)
igv.goto(locus_str)
igv.expand()
# Get locus for each member of overlap group
og_locus = {}
for o in ogroup:
tmp = [c for c in all_locs if c.id == o.attr['name']]
assert len(tmp)==1
og_locus[o.attr['name']] = tmp[0]
# Print out the model coverage
for n,loc in og_locus.iteritems():
print >>sys.stderr, '%s\t%d\t%s' % (n, loc.model_cov(), loc.category())
# Parse user input
z = raw_input('Action to take: ').strip()
if z == '': continue
inputcmd = z.strip().split(' ')
if inputcmd[0] == 'REJECT':
if len(inputcmd) == 1:
# Only max will be kept
st = sorted([loc for n,loc in og_locus.iteritems()], key=lambda x:x.model_cov(), reverse=True)[1:]
loc_ids = [_.id for _ in st]
elif len(inputcmd) == 2:
loc_ids = inputcmd[1].split(',')
else:
assert False
for loc_id in loc_ids:
reject.add(og_locus[loc_id])
elif inputcmd[0] == 'TANDEM':
if len(inputcmd) == 1:
assert len(og_locus)==2, 'More than 2 loci are present'
tandem.append([loc for n,loc in og_locus.iteritems()])
elif len(inputcmd) == 2:
loc_ids = inputcmd[1].split('+')
tandem.append([og_locus[loc_id] for loc_id in loc_ids])
else:
assert False
elif inputcmd[0] == 'DIFF':
n1,n2 = inputcmd[1].split('-')
g1 = og_locus[n1]
g2 = og_locus[n2]
if g1.span()[0] < g2.span()[1]:
g1.shorten(g2.span()[1]+20, g1.span()[1])
elif g1.span()[1] < g2.span()[0]:
g1.shorten(g1.span()[0], g2.span()[0]-20)
else:
print "no overlap!"
print g1
elif inputcmd[0] == 'IGNORE':
continue
else:
assert False, 'Unknown command: "%s"' % inputcmd[0]
# Remove rejected annotations
for rloc in reject:
if rloc in all_locs:
all_locs.remove(rloc)
# Create the tandem annotations
for tgroup in tandem:
tandem_loc = HERVLocus(id=tgroup[0].id)
tandem_loc.internal = list(chain.from_iterable(loc.internal for loc in tgroup))
if tandem_loc.strand() == '+':
tandem_loc.internal.sort(key=lambda x:x.start)
else:
tandem_loc.internal.sort(key=lambda x:x.end, reverse=True)
tandem_loc.find_ltr(args.ltr_files, 1000)
tandem_loc.adjust_overlaps()
tandem_loc.is_tandem = True
all_locs.append(tandem_loc)
# Remove from original
for rloc in tgroup:
all_locs.remove(rloc)
print >>sys.stderr, "After overlap removal:"
print >>sys.stderr, '\n'.join('%s%d' % (cat.ljust(20,' '),count) for cat,count in Counter(c.category() for c in all_locs).most_common())
print >>sys.stderr, '%s%d' % ('Rejected'.ljust(20,' '), len(reject))
if args.igv_preview and len(overlap_groups)>0: os.remove('tmp.gtf')
### Sort loci ########################################################################
bychrom = defaultdict(list)
for loc in all_locs:
bychrom[loc.chrom()].append(loc)
final_locs = []
for chrom in utils.CHROMNAMES:
if chrom in bychrom:
for loc in sorted(bychrom[chrom], key=lambda x:x.span()[0]):
final_locs.append(loc)
for i,loc in enumerate(final_locs):
loc.id = '%s_%04d' % (args.prefix, i+1)
### Rename loci according to cytoband #################################################
# Create GTF with all_locs
with open('tmp.gtf','w') as outh:
for g in utils.sort_gtf(loc.span_gtf() for loc in final_locs):
print >>outh, '\t'.join(g)
p1 = Popen('bedtools intersect -wo -a tmp.gtf -b ../other_sources/cytoband.gtf', shell=True, stdout=PIPE, stderr=PIPE)
out,err = p1.communicate()
os.remove('tmp.gtf')
byband = defaultdict(list)
for ll in out.strip('\n').split('\n'):
f = ll.split('\t')
g1 = GTFLine(f[:9])
g2 = GTFLine(f[9:-1])
band = '%s%s' % (g2.chrom.strip('chr'),g2.attr['gene_id'])
byband[band].append(g1)
namemap = {}
for band,glist in byband.iteritems():
if len(glist) == 1:
namemap[glist[0].attr['name']] = '%s_%s' % (args.prefix, band)
else:
glist.sort(key=lambda x:x.start)
for i,gl in enumerate(glist):
namemap[gl.attr['name']] = '%s_%s%s' % (args.prefix, band, someletters[i])
for loc in final_locs:
loc.locus_name = namemap[loc.id]
### Create annotation files ##########################################################
print >>sys.stderr, "Writing annotation files"
with open('%s.gtf' % args.prefix,'w') as outh:
liter = utils.sort_gtf(chain.from_iterable(loc.each_gtf() for loc in final_locs))
print >>outh, '\n'.join('\t'.join(_) for _ in liter)
# for loc in final_locs:
# print >>outh, '\n'.join('\t'.join(g) for g in loc.each_gtf())
with open('%s_reject.gtf' % args.prefix,'w') as outh:
liter = utils.sort_gtf(chain.from_iterable(loc.each_gtf() for loc in reject))
print >>outh, '\n'.join('\t'.join(_) for _ in liter)
# for loc in reject:
# print >>outh, '\n'.join('\t'.join(g) for g in loc.each_gtf())
with open('%s_span.gtf' % args.prefix,'w') as outh:
for g in utils.sort_gtf(loc.span_gtf() for loc in final_locs):
print >>outh, '\t'.join(g)
with open('%s_table.txt' % args.prefix,'w') as outh:
print >>outh, '\t'.join(['locus_name','id','strand','chrom','start','end','strand','nfeats','width','model_cov','ltr5_model','int_model','ltr3_model'])
for loc in final_locs:
mgtf = GTFLine(loc.span_gtf())
row = [loc.locus_name, loc.id, loc.category(),
mgtf.chrom, mgtf.start, mgtf.end, mgtf.strand,
mgtf.attr['nfeats'], loc.width(), loc.model_cov(),
loc.ltr_up_name(), loc.internal_name(), loc.ltr_down_name(),
]
print >>outh, '\t'.join(str(_) for _ in row)
### Extract sequences ################################################################
if args.get_sequences:
print >>sys.stderr, "Extracting sequences"
genome_fasta = args.genome_fasta # '/Users/bendall/Projects/References/Homo_sapiens/UCSC/hg19/Sequence/WholeGenomeFasta/genome.fa'
genome = dict((s.id,s) for s in SeqIO.parse(genome_fasta,'fasta'))
with open('%s.full.fasta' % args.prefix,'w') as outh:
for loc in final_locs:
gcoord = '%s:%d-%d(%s)' % (loc.chrom(), loc.span()[0], loc.span()[1], loc.strand())
print >>outh, '>%s|%s|%s' % (loc.locus_name, loc.category(), gcoord)
print >>outh, str(loc.entire_sequence(genome).seq)
with open('%s.internal.fasta' % args.prefix,'w') as outh:
for loc in final_locs:
gcoord = '%s:%d-%d(%s)' % (loc.chrom(), min(p.start for p in loc.internal), max(p.end for p in loc.internal), loc.strand())
print >>outh, '>%s_int|%s|%s|%s' % (loc.locus_name, loc.category(), gcoord, loc.format_print_clust())
print >>outh, str(loc.internal_sequence(genome).seq)
with open('%s.5ltr.fasta' % args.prefix,'w') as outh:
for loc in final_locs:
ltrseq = loc.ltr_up_sequence(genome)
if ltrseq:
gcoord = '%s:%d-%d(%s)' % (loc.chrom(), min(p.start for p in loc.ltr_up), max(p.end for p in loc.ltr_up), loc.strand())
print >>outh, '>%s_5LTR|%s|%s' % (loc.locus_name, loc.ltr_up_name(), gcoord)
print >>outh, str(ltrseq.seq)
with open('%s.3ltr.fasta' % args.prefix,'w') as outh:
for loc in final_locs:
ltrseq = loc.ltr_down_sequence(genome)
if ltrseq:
gcoord = '%s:%d-%d(%s)' % (loc.chrom(), min(p.start for p in loc.ltr_down), max(p.end for p in loc.ltr_down), loc.strand())
print >>outh, '>%s_3LTR|%s|%s' % (loc.locus_name, loc.ltr_down_name(), gcoord)
print >>outh, str(ltrseq.seq)
### IGV snapshots ####################################################################
if args.igv_snapshot:
print >>sys.stderr, "Taking IGV snapshots"
igv = IGV()
igv.new()
igv.genome('hg19')
igv.load(os.path.join(os.getcwd(),'../other_sources/rmsk_LTR.hg19.gtf'))
if os.path.isdir('tmp'):
for compare_gtf in glob('tmp/*.gtf'):
igv.load(os.path.join(os.getcwd(), compare_gtf))
igv.load(os.path.join(os.getcwd(),'%s.gtf' % args.prefix))
igv.load(os.path.join(os.getcwd(),'%s_reject.gtf' % args.prefix))
do_snapshots = True
if do_snapshots:
if not os.path.exists(os.path.join(os.getcwd(),'snapshots')):
os.mkdir(os.path.join(os.getcwd(),'snapshots'))
if not os.path.exists(os.path.join(os.getcwd(),'reject')):
os.mkdir(os.path.join(os.getcwd(),'reject'))
categories = ['prototype', 'oneside', 'internal']
for cat in categories:
if not os.path.exists(os.path.join(os.getcwd(),'snapshots/%s' % cat)):
os.mkdir(os.path.join(os.getcwd(),'snapshots/%s' % cat))
if not os.path.exists(os.path.join(os.getcwd(),'reject/%s' % cat)):
os.mkdir(os.path.join(os.getcwd(),'reject/%s' % cat))
for loc in final_locs:
rc,lc = loc.span()
locus_str = '%s:%d-%d' % (loc.chrom(), rc-5000, lc+5000)
print >>sys.stderr, '%s\t%s\t%s' % (loc.locus_name, loc.category(), locus_str)
igv.goto(locus_str)
igv.expand()
if do_snapshots:
igv.snapshotDirectory(os.path.join(os.getcwd(),'snapshots/%s' % loc.category().strip('*') ))
igv.snapshot(filename='%s.png' % loc.locus_name)
for loc in reject:
rc,lc = loc.span()
locus_str = '%s:%d-%d' % (loc.chrom(), rc-5000, lc+5000)
print >>sys.stderr, '%s\t%s\t%s' % (loc.id, loc.category(), locus_str)
igv.goto(locus_str)
igv.expand()
if do_snapshots:
igv.snapshotDirectory(os.path.join(os.getcwd(),'reject/%s' % loc.category().strip('*') ))
igv.snapshot(filename='%s.png' % loc.id)
def main(parser):
args = parser.parse_args()
lines = utils.tab_line_gen(args.infile)
bystrand = {'+': [], '-': []}
for l in lines:
bystrand[l[6]].append(l)
bystrand['+'] = list(utils.sort_gtf(bystrand['+']))
bystrand['-'] = list(utils.sort_gtf(bystrand['-']))
grouped = {'+': [], '-': []}
for strand in ['+', '-']:
score = None
chrom = None
tmp = []
for l in bystrand[strand]:
if score is not None:
if l[5] != score or l[0] != chrom:
grouped[strand].append(tmp)
tmp = []
tmp.append(l)
score = l[5]
chrom = l[0]
gaplens = []
merged = []
for g in grouped['+'] + grouped['-']:
if len(g) == 1:
merged.append(g[0])
else:
mygaps = []
s = ''
for i in range(len(g) - 1):
gaplen = int(g[i + 1][3]) - int(g[i][4])
s += '%s:%s-%s(%s)' % (g[i][0], g[i][3], g[i][4], g[i][6])
s += ' --- %d --- ' % gaplen
mygaps.append(gaplen)
s += '%s:%s-%s(%s)' % (g[-1][0], g[-1][3], g[-1][4], g[-1][6])
if any(g >= QUESTIONABLE for g in mygaps):
continue
else:
gaplens.extend(mygaps)
print >> sys.stderr, s
# spos = min(int(l[3]) for l in g)
# epos = max(int(l[4]) for l in g)
# attrs = [dict(re.findall('(\S+)\s+"([\s\S]+?)";',l[8])) for l in g]
# newline = [g[0][0], 'joined', 'exon', str(spos), str(epos), g[0][5], g[0][6], '.']
# newattr = {'joined': ','.join(a['id'] for a in attrs),
# 'repType': attrs[0]['repType'],
# }
# newline.append(' '.join('%s "%s";' % (k,v) for k,v in newattr.iteritems()))
# merged.append(newline)
if gaplens:
print >> sys.stderr, 'min gap length: %d' % min(gaplens)
print >> sys.stderr, 'mean gap length: %d' % (float(sum(gaplens)) /
len(gaplens))
print >> sys.stderr, 'median gap length: %d' % sorted(gaplens)[
len(gaplens) / 2]
print >> sys.stderr, 'max gap length: %d' % max(gaplens)
else:
print >> sys.stderr, 'No gaps found'
print >> args.outfile, '%d' % max(gaplens)
