def fetchProbeFragments(probe_bed, digest_bed, outfile, lookup_out):
digest_fragments = pysam.TabixFile(digest_bed)
bed = Bed.Bed()
with IOTools.openFile(outfile, "w") as outf, \
IOTools.openFile(lookup_out,"w") as lookup:
lookup.write("probe\tfragment\n")
for probe in Bed.iterator(IOTools.openFile(probe_bed)):
frag = digest_fragments.fetch(probe.contig,
probe.start,
probe.end,
parser=pysam.asBed())
frag = list(frag)
if not len(frag) == 1:
E.warn("%i fragments found for probe %s, skipping" %
(len(frag), probe.name))
continue
frag = frag[0]
bed.start = frag.start
bed.end = frag.end
bed.contig = frag.contig
bed["name"] = probe.name
bed["score"] = "."
bed["strand"] = "+"
lookup.write("%s\t%s\n" % (probe.name, frag.name))
outf.write(str(bed) + "\n")
def exportSequencesFromBedFile( infile, outfile, masker = None, mode = "intervals" ):
'''export sequences for intervals in :term:`bed`-formatted *infile*
to :term:`fasta` formatted *outfile*
'''
track = P.snip( infile, ".bed.gz" )
fasta = IndexedFasta.IndexedFasta( os.path.join( PARAMS["genome_dir"], PARAMS["genome"] ) )
outs = IOTools.openFile( outfile, "w")
ids, seqs = [], []
for bed in Bed.setName(Bed.iterator( IOTools.openFile(infile) )):
lcontig = fasta.getLength( bed.contig )
if mode == "intervals":
seqs.append( fasta.getSequence( bed.contig, "+", bed.start, bed.end) )
ids.append( "%s_%s %s:%i..%i" % (track, bed.name, bed.contig, bed.start, bed.end) )
elif mode == "leftright":
l = bed.end - bed.start
start, end = max(0,bed.start-l), bed.end-l
ids.append( "%s_%s_l %s:%i..%i" % (track, bed.name, bed.contig, start, end) )
seqs.append( fasta.getSequence( bed.contig, "+", start, end) )
start, end = bed.start+l, min(lcontig,bed.end+l)
ids.append( "%s_%s_r %s:%i..%i" % (track, bed.name, bed.contig, start, end) )
seqs.append( fasta.getSequence( bed.contig, "+", start, end) )
masked = maskSequences( seqs, masker )
outs.write("\n".join( [ ">%s\n%s" % (x,y) for x,y in zip(ids, masked) ] ) )
outs.close()
def annotateCpGIslands(infiles, outfile):
'''annotate transcript by absence/presence of CpG islands
'''
cpgfile, tssfile = infiles
cpg = Bed.readAndIndex(IOTools.openFile(cpgfile))
extension_upstream = PARAMS["cpg_search_upstream"]
extension_downstream = PARAMS["cpg_search_downstream"]
c = E.Counter()
outf = IOTools.openFile(outfile, "w")
outf.write(
"transcript_id\tstrand\tstart\tend\trelative_start\trelative_end\n")
for tss in Bed.iterator(IOTools.openFile(tssfile)):
c.tss_total += 1
if tss.strand == "+":
start, end = tss.start - extension_upstream, tss.start + extension_downstream
else:
start, end = tss.end - extension_downstream, tss.end + extension_upstream
try:
matches = list(cpg[tss.contig].find(start, end))
except KeyError:
c.promotor_without_matches += 1
continue
if len(matches) == 0:
c.promotor_without_matches += 1
continue
c.promotor_output += 1
for match in matches:
c.matches_total += 1
genome_start, genome_end, x = match
l = genome_end - genome_start
# get relative location of match
if tss.strand == "+":
relative_start = genome_start - tss.start
else:
relative_start = tss.end - genome_end
relative_end = relative_start + l
outf.write("\t".join(
map(str, (tss.name, tss.strand, genome_start, genome_end,
relative_start, relative_end))) + "\n")
c.matches_output += 1
outf.close()
with IOTools.openFile(outfile + ".summary", "w") as outf:
outf.write("category\tcounts\n")
outf.write(c.asTable() + "\n")
E.info(c)
def getProbeFragments(probe_bed, digest_bed, outfile,
lookup_out):
# First find the length of the restriction enzyme cut, required to obtain the start and end coordinates
# from the pregenerated file.
# First iteration, no comparison
first_iteration = True
length_RE_cut = 0
last_bed = None
for bed_digest in Bed.iterator(IOTools.openFile(digest_bed)):
if(first_iteration):
first_iteration = False
else:
# If they are in the same contig they can be compared
if(bed_digest.contig == last_bed.contig):
length_RE_cut = bed_digest.start - last_bed.end
break
last_bed = bed_digest
digest_fragments = pysam.TabixFile(digest_bed)
bed = Bed.Bed()
with IOTools.openFile(outfile, "w") as outf, \
IOTools.openFile(lookup_out,"w") as lookup:
lookup.write("probe\tfragment\n")
for probe in Bed.iterator(IOTools.openFile(probe_bed)):
frag = digest_fragments.fetch(probe.contig,
probe.start,
probe.end,
parser=pysam.asBed())
frag = list(frag)
if not len(frag) == 1:
E.warn("%i fragments found for probe %s, skipping" %
(len(frag), probe.name))
continue
frag = frag[0]
# The restriction enzyme cut on the left side of the fragment
# is the end site of the last restriction enzyme fragment + 1
# (+1 because according to the manual coordinates are specified
# in 1-origin for the bed start.)
bed.start = frag.start-length_RE_cut+1
bed.end = frag.end+length_RE_cut
bed.contig = frag.contig
bed["name"] = probe.name
bed["score"] = "."
bed["strand"] = "+"
lookup.write("%s\t%s\n" % (probe.name, frag.name))
outf.write(str(bed) + "\n")
def annotateCpGIslands( infiles, outfile ):
'''annotate transcript by absence/presence of CpG islands
'''
cpgfile, tssfile = infiles
cpg = Bed.readAndIndex( IOTools.openFile( cpgfile ) )
extension_upstream = PARAMS["cpg_search_upstream"]
extension_downstream = PARAMS["cpg_search_downstream"]
c = E.Counter()
outf = IOTools.openFile( outfile, "w" )
outf.write("transcript_id\tstrand\tstart\tend\trelative_start\trelative_end\n" )
for tss in Bed.iterator(IOTools.openFile( tssfile ) ):
c.tss_total += 1
if tss.strand == "+":
start, end = tss.start - extension_upstream, tss.start + extension_downstream
else:
start, end = tss.end - extension_downstream, tss.end + extension_upstream
try:
matches = list(cpg[tss.contig].find( start, end ))
except KeyError:
c.promotor_without_matches += 1
continue
if len(matches) == 0:
c.promotor_without_matches += 1
continue
c.promotor_output += 1
for match in matches:
c.matches_total += 1
genome_start, genome_end, x = match
l = genome_end - genome_start
# get relative location of match
if tss.strand == "+":
relative_start = genome_start - tss.start
else:
relative_start = tss.end - genome_end
relative_end = relative_start + l
outf.write( "\t".join( map(str, (
tss.name, tss.strand,
genome_start, genome_end,
relative_start, relative_end ))) + "\n" )
c.matches_output += 1
outf.close()
with IOTools.openFile( outfile + ".summary", "w" ) as outf:
outf.write ("category\tcounts\n" )
outf.write( c.asTable() + "\n" )
E.info( c )
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if not argv:
argv = sys.argv
# setup command line parser
parser = E.OptionParser(
version="%prog version: $Id: bed2graph.py 2861 2010-02-23 17:36:32Z andreas $", usage=globals()["__doc__"])
parser.add_option("-o", "--output", dest="output", type="choice",
choices=("full", "name"),
help="output either ``full`` overlapping entries, only the ``name``s. [default=%default].")
parser.set_defaults(
output="full",
)
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
if len(args) != 2:
raise ValueError("two arguments required")
if args[0] == "-":
infile1 = options.stdin
else:
infile1 = IOTools.openFile(args[0], "r")
infile2 = IOTools.openFile(args[1], "r")
idx = Bed.readAndIndex(infile2, with_values=True)
output = options.output
outfile = options.stdout
if output == "name":
outfile.write("name1\tname2\n")
outf = lambda x: x.fields[0]
else:
outf = str
for bed in Bed.iterator(infile1):
try:
overlaps = idx[bed.contig].find(bed.start, bed.end)
except (KeyError, IndexError):
# ignore missing contig and zero length intervals
continue
for o in overlaps:
outfile.write("\t".join((outf(bed), outf(o[2]))) + "\n")
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if not argv:
argv = sys.argv
# setup command line parser
parser = E.OptionParser(
version="%prog version: $Id: bed2graph.py 2861 2010-02-23 17:36:32Z andreas $", usage=globals()["__doc__"])
parser.add_option("-o", "--output-section", dest="output", type="choice",
choices=("full", "name"),
help="output either ``full`` overlapping entries, only the ``name``s. [default=%default].")
parser.set_defaults(
output="full",
)
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
if len(args) != 2:
raise ValueError("two arguments required")
if args[0] == "-":
infile1 = options.stdin
else:
infile1 = IOTools.openFile(args[0], "r")
infile2 = IOTools.openFile(args[1], "r")
idx = Bed.readAndIndex(infile2, with_values=True)
output = options.output
outfile = options.stdout
if output == "name":
outfile.write("name1\tname2\n")
outf = lambda x: x.fields[0]
else:
outf = str
for bed in Bed.iterator(infile1):
try:
overlaps = idx[bed.contig].find(bed.start, bed.end)
except (KeyError, IndexError):
# ignore missing contig and zero length intervals
continue
for o in overlaps:
outfile.write("\t".join((outf(bed), outf(o[2]))) + "\n")
E.Stop()
def _count(self, filename, idx):
'''count filename against idx.'''
overlapping_genes = set()
genes = set()
# iterate over exons
infile = IOTools.openFile(filename, "r")
it = Bed.bed_iterator(infile)
nexons, nexons_overlapping = 0, 0
nbases, nbases_overlapping = 0, 0
for this in it:
nexons += 1
nbases += this.end - this.start
try:
intervals = list(
idx[this.contig].find(max(0, this.start), this.end))
except KeyError:
continue
except Exception, msg:
raise Exception(
"error while processing %s, msg=%s" % (filename, msg))
if len(intervals) == 0:
continue
nexons_overlapping += 1
start, end = this.start, this.end
counts = numpy.zeros(end - start, numpy.int)
for other_start, other_end, other_value in intervals:
for x in range(max(start, other_start) - start, min(end, other_end) - start):
counts[x] += 1
nbases_overlapping += sum([1 for x in counts if x > 0])
def aggregateWindowsReadCounts(infiles, outfile, regex="(.*)\..*"):
'''aggregate several results from coverageBed
into a single file.
*regex* is used to extract the track name from the filename.
The default removes any suffix.
coverageBed outputs the following columns:
1 Contig
2 Start
3 Stop
4 Name
5 The number of features in A that overlapped (by at least one
base pair) the B interval.
6 The number of bases in B that had non-zero coverage from features in A.
7 The length of the entry in B.
8 The fraction of bases in B that had non-zero coverage from
features in A.
For bed: use column 5
For bed6: use column 7
For bed12: use column 13
Windows without any counts will not be output.
'''
# get bed format
bed_columns = Bed.getNumColumns(infiles[0])
# +1 as awk is 1-based
column = bed_columns - 4 + 1
src = " ".join([
'''<( zcat %s | awk '{printf("%%s:%%i-%%i\\t%%i\\n", $1,$2,$3,$%s );}' ) '''
% (x, column) for x in infiles
])
tmpfile = P.getTempFilename(".")
statement = '''paste %(src)s > %(tmpfile)s'''
P.run()
# build track names
tracks = [
re.search(regex, os.path.basename(x)).groups()[0] for x in infiles
]
outf = IOTools.openFile(outfile, "w")
outf.write("interval_id\t%s\n" % "\t".join(tracks))
for line in open(tmpfile, "r"):
data = line[:-1].split("\t")
genes = list(set([data[x] for x in range(0, len(data), 2)]))
values = [int(data[x]) for x in range(1, len(data), 2)]
if sum(values) == 0:
continue
assert len(genes) == 1, \
"paste command failed, wrong number of genes per line: '%s'" % line
outf.write("%s\t%s\n" % (genes[0], "\t".join(map(str, values))))
outf.close()
os.unlink(tmpfile)
def fetchProbeFragments(probe_bed, digest_bed, outfile,
lookup_out):
digest_fragments = pysam.TabixFile(digest_bed)
bed = Bed.Bed()
with IOTools.openFile(outfile, "w") as outf, \
IOTools.openFile(lookup_out,"w") as lookup:
lookup.write("probe\tfragment\n")
for probe in Bed.iterator(IOTools.openFile(probe_bed)):
frag = digest_fragments.fetch(probe.contig,
probe.start,
probe.end,
parser=pysam.asBed())
frag = list(frag)
if not len(frag) == 1:
E.warn("%i fragments found for probe %s, skipping" %
(len(frag), probe.name))
continue
frag = frag[0]
bed.start = frag.start
bed.end = frag.end
bed.contig = frag.contig
bed["name"] = probe.name
bed["score"] = "."
bed["strand"] = "+"
lookup.write("%s\t%s\n" % (probe.name, frag.name))
outf.write(str(bed) + "\n")
def aggregateWindowsReadCounts(infiles,
outfile,
regex="(.*)\..*"):
'''aggregate several results from coverageBed
into a single file.
*regex* is used to extract the track name from the filename.
The default removes any suffix.
coverageBed outputs the following columns:
1 Contig
2 Start
3 Stop
4 Name
5 The number of features in A that overlapped (by at least one
base pair) the B interval.
6 The number of bases in B that had non-zero coverage from features in A.
7 The length of the entry in B.
8 The fraction of bases in B that had non-zero coverage from
features in A.
For bed: use column 5
For bed6: use column 7
For bed12: use column 13
Windows without any counts will not be output.
'''
# get bed format
bed_columns = Bed.getNumColumns(infiles[0])
# +1 as awk is 1-based
column = bed_columns - 4 + 1
src = " ".join(['''<( zcat %s |
awk '{printf("%%s:%%i-%%i\\t%%i\\n", $1,$2,$3,$%s );}' ) ''' %
(x, column) for x in infiles])
tmpfile = P.getTempFilename(".")
statement = '''paste %(src)s > %(tmpfile)s'''
P.run()
# build track names
tracks = [re.search(regex, os.path.basename(x)).groups()[0]
for x in infiles]
outf = IOTools.openFile(outfile, "w")
outf.write("interval_id\t%s\n" % "\t".join(tracks))
for line in open(tmpfile, "r"):
data = line[:-1].split("\t")
genes = list(set([data[x] for x in range(0, len(data), 2)]))
values = [int(data[x]) for x in range(1, len(data), 2)]
if sum(values) == 0:
continue
assert len(genes) == 1, \
"paste command failed, wrong number of genes per line: '%s'" % line
outf.write("%s\t%s\n" % (genes[0], "\t".join(map(str, values))))
outf.close()
os.unlink(tmpfile)
def quantifyAnomolies(bam, probes, outfile):
bamfile = pysam.AlignmentFile(bam)
results = dict()
mapped = bamfile.mapped
total = 0
seeks = 0
for probe in Bed.iterator(IOTools.openFile(probes)):
c = collections.Counter()
for read in bamfile.fetch(probe.contig,
probe.start,
probe.end,
multiple_iterators=True):
if read.is_unmapped:
continue
c["total"] += 1
if not (read.is_secondary or read.is_supplementary):
c["primary"] += 1
else:
continue
if read.pos < (probe.start - 4) or read.aend > (probe.end + 4):
c["undigested"] += 1
if read.is_read1:
c["read1"] += 1
if not read.mate_is_unmapped:
c["paired"] += 1
if read.is_read1 and (read.mpos >= probe.start
and read.mpos <= probe.end):
c["self_lig"] += 1
if (total + c["total"] % 10000) == 0:
E.debug("%s/%s done" % (total + c["total"], mapped))
E.debug("%s processed, %i found" % (probe.name, c["total"]))
results[probe.name] = c
total += c["total"]
headers = [
"Probe", "total", "primary", "undigested", "read1", "paired",
"self_lig"
]
with IOTools.openFile(outfile, "w") as outf:
outf.write("\t".join(headers) + "\n")
for probe in results:
outf.write("\t".join(
[probe] + [str(results[probe][col])
for col in headers[1:]]) + "\n")
def sites2fragments(infile, genomefile, outfile):
'''Convert bedfile of deigestion sites into bedfile of fragments'''
contig_lengths = {
line.split()[0]: int(line.split()[1][:-1])
for line in IOTools.openFile(genomefile)
}
last_end = 0
last_contig = None
name = 0
new_bed = Bed.Bed()
new_bed["strand"] = "+"
new_bed["score"] = "."
with IOTools.openFile(outfile, "w") as outf:
for bed in Bed.iterator(IOTools.openFile(infile)):
if last_contig is not None and not bed.contig == last_contig:
name += 1
new_bed.start = last_end
new_bed.contig = last_contig
new_bed.end = contig_lengths[bed.contig]
new_bed["name"] = str(name)
outf.write(str(new_bed) + "\n")
last_end = 0
last_contig = bed.contig
new_bed.contig = last_contig
new_bed.start = last_end
new_bed.end = bed.start
name += 1
new_bed["name"] = str(name)
outf.write(str(new_bed) + "\n")
last_end = bed.end
name += 1
new_bed.start = last_end
new_bed.contig = last_contig
new_bed.end = contig_lengths[bed.contig]
new_bed["name"] = str(name)
outf.write(str(new_bed) + "\n")
pysam.tabix_index(outfile, force=True, preset="bed")
def quantifyAnomolies(bam, probes, outfile):
bamfile = pysam.AlignmentFile(bam)
results = dict()
mapped = bamfile.mapped
total = 0
seeks = 0
for probe in Bed.iterator(IOTools.openFile(probes)):
c = collections.Counter()
for read in bamfile.fetch(probe.contig, probe.start, probe.end,
multiple_iterators=True):
if read.is_unmapped:
continue
c["total"] += 1
if not (read.is_secondary or read.is_supplementary):
c["primary"] += 1
else:
continue
if read.pos < (probe.start-4) or read.aend > (probe.end +4):
c["undigested"] += 1
if read.is_read1:
c["read1"] += 1
if not read.mate_is_unmapped:
c["paired"] += 1
if read.is_read1 and (
read.mpos >= probe.start and read.mpos <= probe.end):
c["self_lig"] += 1
if (total + c["total"] % 10000) == 0:
E.debug("%s/%s done" % (total + c["total"], mapped))
E.debug("%s processed, %i found" % (probe.name, c["total"]))
results[probe.name] = c
total += c["total"]
headers = ["Probe", "total", "primary", "undigested",
"read1", "paired", "self_lig"]
with IOTools.openFile(outfile, "w") as outf:
outf.write("\t".join(headers) + "\n")
for probe in results:
outf.write("\t".join(
[probe]+[str(results[probe][col])
for col in headers[1:]]) + "\n")
def main( argv = None ):
if argv == None: argv = sys.argv
parser = E.OptionParser( version = "%prog version: $Id: gtf2table.py 2888 2010-04-07 08:48:36Z andreas $", usage = globals()["__doc__"])
parser.add_option("-g", "--genome-file", dest="genome_file", type="string",
help="filename with genome [default=%default]." )
parser.add_option("-n", "--per-name", dest="per_name", action="store_true",
help="compute counts per name [default=%default]." )
parser.add_option("-c", "--per-contig", dest="per_contig", action="store_true",
help="compute counts per contig [default=%default]." )
parser.add_option("-t", "--per-track", dest="per_track", action="store_true",
help="compute counts per track [default=%default]." )
parser.set_defaults(
genome_file = None,
per_name = False,
per_track = False,
)
(options, args) = E.Start( parser, argv )
# get files
if options.genome_file:
fasta = IndexedFasta.IndexedFasta( options.genome_file )
else:
fasta = None
counts = collections.defaultdict( Counter )
if options.per_track:
keyf = lambda x: x.track
elif options.per_name:
keyf = lambda x: x.name
elif options.per_contig:
keyf = lambda x: x.contig
else:
keyf = lambda x: "all"
for bed in Bed.iterator(options.stdin):
counts[keyf(bed)].add( bed )
outf = options.stdout
key = "track"
outf.write( "%s\t%s\n" % (key, "\t".join( Counter.headers) ))
for key, count in counts.iteritems():
outf.write( "%s\t%s\n" % ( key, str(count)) )
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
# setup command line parser
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option("-t", "--test", dest="test", type="string",
help="supply help")
parser.add_option("--regex-filename", dest="re_name", type="string",
help="regex for filename component to be used "
"as the annotation label")
parser.set_defaults(
re_name="(.+)",
)
(options, args) = E.Start(parser, argv=argv)
infiles = argv[-1]
bed_files = infiles.split(",")
if len(bed_files) == 1:
raise IOError("Only one file detected, cannot merge "
"a single bed file")
else:
pass
# get the regex for annotation names,
rx = re.compile(options.re_name)
annot_names = [[y for y in rx.search(x).groups()] for x in bed_files]
annot_names = list(itertools.chain(*annot_names))
# output as BED4 format: chr, start, end, name
for fx in range(len(bed_files)):
bfile = bed_files[fx]
with IOTools.openFile(bfile, "r") as ofile:
intervals = Bed.iterator(ofile)
track_name = [bx for bx in annot_names if re.search(bx, bfile)][0]
for entry in intervals:
entry.__setitem__("name", track_name)
options.stdout.write("%s\t%s\t%s\t%s\n" % (entry.contig,
entry.start,
entry.end,
entry.name))
# write footer and output benchmark information.
E.Stop()
def aggregateWindowsReadCounts(infiles, outfile):
'''aggregate tag counts for each window.
coverageBed outputs the following columns:
1) Contig
2) Start
3) Stop
4) Name
5) The number of features in A that overlapped (by at least one base pair) the B interval.
6) The number of bases in B that had non-zero coverage from features in A.
7) The length of the entry in B.
8) The fraction of bases in B that had non-zero coverage from features in A.
For bed: use column 5
For bed6: use column 7
For bed12: use column 13
Tiles with no counts will not be output.
'''
to_cluster = True
# get bed format
bed_columns = Bed.getNumColumns(infiles[0])
# +1 as awk is 1-based
column = bed_columns - 4 + 1
src = " ".join([
'''<( zcat %s | awk '{printf("%%s:%%i-%%i\\t%%i\\n", $1,$2,$3,$%s );}' ) '''
% (x, column) for x in infiles
])
tmpfile = P.getTempFilename(".")
statement = '''paste %(src)s > %(tmpfile)s'''
P.run()
tracks = [re.sub("\..*", '', os.path.basename(x)) for x in infiles]
outf = IOTools.openFile(outfile, "w")
outf.write("interval_id\t%s\n" % "\t".join(tracks))
for line in open(tmpfile, "r"):
data = line[:-1].split("\t")
genes = list(set([data[x] for x in range(0, len(data), 2)]))
values = [int(data[x]) for x in range(1, len(data), 2)]
if sum(values) == 0: continue
assert len(
genes
) == 1, "paste command failed, wrong number of genes per line: '%s'" % line
outf.write("%s\t%s\n" % (genes[0], "\t".join(map(str, values))))
outf.close()
os.unlink(tmpfile)
def countTagsInClusters(bedfile, bamfile, outfile):
bam = pysam.AlignmentFile(bamfile)
outlines = []
for bed in Bed.iterator(IOTools.openFile(bedfile)):
interval = (bed.start, bed.end)
counts = iCLIP.count_intervals(bam, [interval], bed.contig).sum()
outlines.append(["%s:%i-%i" % (bed.contig, bed.start, bed.end), str(counts)])
IOTools.writeLines(outfile, outlines, header=["position","count"])
def exportSequencesFromBedFile(infile, outfile, masker=None, mode="intervals"):
'''export sequences for intervals in :term:`bed`-formatted *infile*
to :term:`fasta` formatted *outfile*
'''
track = P.snip(infile, ".bed.gz")
fasta = IndexedFasta.IndexedFasta(
os.path.join(P.get_params()["genome_dir"],
P.get_params()["genome"]))
outs = IOTools.open_file(outfile, "w")
ids, seqs = [], []
for bed in Bed.setName(Bed.iterator(IOTools.open_file(infile))):
lcontig = fasta.getLength(bed.contig)
if mode == "intervals":
seqs.append(fasta.getSequence(bed.contig, "+", bed.start, bed.end))
ids.append("%s_%s %s:%i..%i" %
(track, bed.name, bed.contig, bed.start, bed.end))
elif mode == "leftright":
l = bed.end - bed.start
start, end = max(0, bed.start - l), bed.end - l
ids.append("%s_%s_l %s:%i..%i" %
(track, bed.name, bed.contig, start, end))
seqs.append(fasta.getSequence(bed.contig, "+", start, end))
start, end = bed.start + l, min(lcontig, bed.end + l)
ids.append("%s_%s_r %s:%i..%i" %
(track, bed.name, bed.contig, start, end))
seqs.append(fasta.getSequence(bed.contig, "+", start, end))
masked = maskSequences(seqs, masker)
outs.write("\n".join([">%s\n%s" % (x, y) for x, y in zip(ids, masked)]))
outs.close()
def countTagsInClusters(bedfile, bamfile, outfile):
bam = pysam.AlignmentFile(bamfile)
outlines = []
for bed in Bed.iterator(IOTools.openFile(bedfile)):
interval = (bed.start, bed.end)
counts = iCLIP.count_intervals(bam, [interval], bed.contig).sum()
outlines.append(
["%s:%i-%i" % (bed.contig, bed.start, bed.end),
str(counts)])
IOTools.writeLines(outfile, outlines, header=["position", "count"])
def buildAlignmentSizes(infiles, outfile):
'''
use bed files to sum the total number of bases
that are aligned to the genomes
'''
outf = open(outfile, "w")
outf.write("genome\tsize\n")
for infile in infiles:
genome = P.snip(os.path.basename(infile), ".bed.gz")
c = 0
inf = IOTools.openFile(infile)
for bed in Bed.iterator(inf):
c += bed.end - bed.start
outf.write("%s\t%s\n" % (genome, str(c)))
outf.close()
def buildAlignmentSizes(infiles, outfile):
'''
use bed files to sum the total number of bases
that are aligned to the genomes
'''
outf = open(outfile, "w")
outf.write("genome\tsize\n")
for infile in infiles:
genome = P.snip(os.path.basename(infile), ".bed.gz")
c = 0
inf = IOTools.openFile(infile)
for bed in Bed.iterator(inf):
c += bed.end - bed.start
outf.write("%s\t%s\n" % (genome, str(c)))
outf.close()
def buildQuicksectMask(bed_file):
'''return Quicksect object containing the regions specified
takes a bed file listing the regions to mask
'''
mask = IndexedGenome.Quicksect()
n_regions = 0
for bed in Bed.iterator(IOTools.openFile(bed_file)):
# it is neccessary to extend the region to make an accurate mask
mask.add(bed.contig, (bed.start - 1), (bed.end + 1), 1)
n_regions += 1
E.info("Built Quicksect mask for %i regions" % n_regions)
return(mask)
def buildQuicksectMask(bed_file):
'''return Quicksect object containing the regions specified
takes a bed file listing the regions to mask
'''
mask = IndexedGenome.Quicksect()
n_regions = 0
for bed in Bed.iterator(IOTools.openFile(bed_file)):
# it is neccessary to extend the region to make an accurate mask
mask.add(bed.contig, (bed.start - 1), (bed.end + 1), 1)
n_regions += 1
E.info("Built Quicksect mask for %i regions" % n_regions)
return(mask)
def bedsFromList(data):
''' takes a list of data and returns a bed object'''
for interval in data:
bed = Bed.Bed()
try:
bed.contig, bed.start, bed.end = \
interval[0], int(interval[1]), int(interval[2])
except IndexError:
raise ValueError("Insufficient fields to generate bed entry")
except ValueError:
raise ValueError("Fields 2 and 3 must be integer")
bed.fields = interval[3:]
yield bed
def aggregateWindowsReadCounts( infiles, outfile ):
'''aggregate tag counts for each window.
coverageBed outputs the following columns:
1) Contig
2) Start
3) Stop
4) Name
5) The number of features in A that overlapped (by at least one base pair) the B interval.
6) The number of bases in B that had non-zero coverage from features in A.
7) The length of the entry in B.
8) The fraction of bases in B that had non-zero coverage from features in A.
For bed: use column 5
For bed6: use column 7
For bed12: use column 13
Tiles with no counts will not be output.
'''
to_cluster = True
# get bed format
bed_columns = Bed.getNumColumns( infiles[0] )
# +1 as awk is 1-based
column = bed_columns - 4 + 1
src = " ".join( [ '''<( zcat %s | awk '{printf("%%s:%%i-%%i\\t%%i\\n", $1,$2,$3,$%s );}' ) ''' % (x,column) for x in infiles] )
tmpfile = P.getTempFilename( "." )
statement = '''paste %(src)s > %(tmpfile)s'''
P.run()
tracks = [ re.sub( "\..*", '', os.path.basename(x) ) for x in infiles ]
outf = IOTools.openFile( outfile, "w")
outf.write( "interval_id\t%s\n" % "\t".join( tracks ) )
for line in open( tmpfile, "r" ):
data = line[:-1].split("\t")
genes = list(set([ data[x] for x in range(0,len(data), 2 ) ]))
values = [ int(data[x]) for x in range(1,len(data), 2 ) ]
if sum(values) == 0: continue
assert len(genes) == 1, "paste command failed, wrong number of genes per line: '%s'" % line
outf.write( "%s\t%s\n" % (genes[0], "\t".join(map(str, values) ) ) )
outf.close()
os.unlink(tmpfile)
def sites2fragments(infile, genomefile, outfile):
'''Convert bedfile of deigestion sites into bedfile of fragments'''
contig_lengths = {line.split()[0]: int(line.split()[1][:-1])
for line in IOTools.openFile(genomefile)}
last_end = 0
last_contig = None
name = 0
new_bed = Bed.Bed()
new_bed["strand"] = "+"
new_bed["score"] = "."
with IOTools.openFile(outfile, "w") as outf:
for bed in Bed.iterator(IOTools.openFile(infile)):
if last_contig is not None and not bed.contig == last_contig:
name += 1
new_bed.start = last_end
new_bed.contig = last_contig
new_bed.end = contig_lengths[bed.contig]
new_bed["name"] = str(name)
outf.write(str(new_bed) + "\n")
last_end = 0
last_contig = bed.contig
new_bed.contig = last_contig
new_bed.start = last_end
new_bed.end = bed.start
name += 1
new_bed["name"] = str(name)
outf.write(str(new_bed) + "\n")
last_end = bed.end
name += 1
new_bed.start = last_end
new_bed.contig = last_contig
new_bed.end = contig_lengths[bed.contig]
new_bed["name"] = str(name)
outf.write(str(new_bed) + "\n")
pysam.tabix_index(outfile, force=True, preset="bed")
def __init__(self, filename, *args, **kwargs ):
assert filename != None, "please supply filename for CounterOverlap"
Counter.__init__(self, *args, **kwargs )
self.filename = filename
E.info( "reading intervals from %s" % self.filename )
self.index = Bed.readAndIndex( IOTools.openFile( self.filename, "r"),
per_track = True )
E.info( "read intervals for %s tracks" % len(self.index) )
self.tracks = self.index.keys()
self.headers = []
for track in self.tracks:
self.headers.extend( ["%s_nover" % track, "%s_bases" % track] )
def __init__(self, filename, *args, **kwargs ):
assert filename != None, "please supply filename for CounterOverlap"
Counter.__init__(self, *args, **kwargs )
self.filename = filename
E.info( "reading intervals from %s" % self.filename )
self.index = Bed.readAndIndex( IOTools.openFile( self.filename, "r"),
per_track = True )
E.info( "read intervals for %s tracks" % len(self.index) )
self.tracks = self.index.keys()
self.headers = []
for track in self.tracks:
self.headers.extend( ["%s_nover" % track, "%s_bases" % track] )
def transcript2bed12(transcript):
new_entry = Bed.Bed()
start = min(entry.start for entry in transcript)
end = max(entry.end for entry in transcript)
try:
thickStart = min(entry.start for entry in transcript
if entry.feature == "CDS")
thickEnd = max(entry.end for entry in transcript
if entry.feature == "CDS")
except ValueError:
# if there is no CDS, then set first base of transcript as
# start
if transcript[0].strand == "-":
thickStart = end
thickEnd = end
else:
thickStart = start
thickEnd = start
exons = GTF.asRanges(transcript, "exon")
exon_starts = [es - start for (es, ee) in exons]
exon_lengths = [ee - es for (es, ee) in exons]
exon_count = len(exons)
new_entry.contig = transcript[0].contig
new_entry.start = start
new_entry.end = end
new_entry["strand"] = transcript[0].strand
new_entry["name"] = transcript[0].transcript_id
new_entry["thickStart"] = thickStart
new_entry["thickEnd"] = thickEnd
new_entry["blockCount"] = exon_count
new_entry["blockStarts"] = ",".join(map(str, exon_starts))
new_entry["blockSizes"] = ",".join(map(str, exon_lengths))
return new_entry
def windows2bed12(windows, contig, strand, name, score):
'''Convert a list of intervals into a single bed12 entry '''
windows = sorted(windows)
entry = Bed.Bed()
#if strand == "-":
# windows = [(y+1, x+1) for x, y in windows]
# windows = sorted(windows)
#else:
# windows = sorted(windows)
entry.start = int(windows[0][0])
entry.end = int(windows[-1][1])
entry.contig = contig
blockCount = int(len(windows))
blockSizes = ",".join(
[str(int(window[1] - window[0])) for window in windows])
blockStarts = ",".join(
[str(int(window[0] - windows[0][0])) for window in windows])
thickStart = int(entry.start)
thickEnd = int(entry.end)
itemRGB = "255,0,0"
entry.fields = [
name, score, strand, thickStart, thickEnd, itemRGB, blockCount,
blockSizes, blockStarts
]
assert entry.end - entry.start > 0, "Malformed Bed entry entry size less than zero"
assert all([blockSize > 0 for blockSize in
map(int, blockSizes.split(","))]), \
"Malformed Bed entry, at least one block size less than zero"
assert all([entry.start + blockStart <= entry.end
for blockStart in map(int,blockStarts.split(","))]), \
"Malformed Bed entry: block start after end of entry"
return entry
def makeIntervalCorrelation(infiles, outfile, field, reference):
'''compute correlation of interval properties between sets
'''
dbhandle = sqlite3.connect(PARAMS["database_name"])
tracks, idx = [], []
for infile in infiles:
track = P.snip(infile, ".bed.gz")
tablename = "%s_intervals" % P.tablequote(track)
cc = dbhandle.cursor()
statement = "SELECT contig, start, end, %(field)s FROM %(tablename)s" % locals(
)
cc.execute(statement)
ix = IndexedGenome.IndexedGenome()
for contig, start, end, peakval in cc:
ix.add(contig, start, end, peakval)
idx.append(ix)
tracks.append(track)
outs = IOTools.openFile(outfile, "w")
outs.write("contig\tstart\tend\tid\t" + "\t".join(tracks) + "\n")
for bed in Bed.iterator(infile=IOTools.openFile(reference, "r")):
row = []
for ix in idx:
try:
intervals = list(ix.get(bed.contig, bed.start, bed.end))
except KeyError:
row.append("")
continue
if len(intervals) == 0:
peakval = ""
else:
peakval = str((max([x[2] for x in intervals])))
row.append(peakval)
outs.write(str(bed) + "\t" + "\t".join(row) + "\n")
outs.close()
def makeIntervalCorrelation(infiles, outfile, field, reference):
'''compute correlation of interval properties between sets
'''
dbhandle = sqlite3.connect(PARAMS["database_name"])
tracks, idx = [], []
for infile in infiles:
track = P.snip(infile, ".bed.gz")
tablename = "%s_intervals" % P.tablequote(track)
cc = dbhandle.cursor()
statement = "SELECT contig, start, end, %(field)s FROM %(tablename)s" % locals(
)
cc.execute(statement)
ix = IndexedGenome.IndexedGenome()
for contig, start, end, peakval in cc:
ix.add(contig, start, end, peakval)
idx.append(ix)
tracks.append(track)
outs = IOTools.openFile(outfile, "w")
outs.write("contig\tstart\tend\tid\t" + "\t".join(tracks) + "\n")
for bed in Bed.iterator(infile=IOTools.openFile(reference, "r")):
row = []
for ix in idx:
try:
intervals = list(ix.get(bed.contig, bed.start, bed.end))
except KeyError:
row.append("")
continue
if len(intervals) == 0:
peakval = ""
else:
peakval = str((max([x[2] for x in intervals])))
row.append(peakval)
outs.write(str(bed) + "\t" + "\t".join(row) + "\n")
outs.close()
def _count(self, filename, idx):
'''count filename against idx.'''
overlapping_genes = set()
genes = set()
# iterate over exons
infile = IOTools.openFile(filename, "r")
it = Bed.bed_iterator(infile)
nexons, nexons_overlapping = 0, 0
nbases, nbases_overlapping = 0, 0
for this in it:
nexons += 1
nbases += this.end - this.start
try:
intervals = list(idx[this.contig].find(max(0, this.start),
this.end))
except KeyError:
continue
except Exception as msg:
raise Exception("error while processing %s, msg=%s" %
(filename, msg))
if len(intervals) == 0:
continue
nexons_overlapping += 1
start, end = this.start, this.end
counts = numpy.zeros(end - start, numpy.int)
for other_start, other_end, other_value in intervals:
for x in range(
max(start, other_start) - start,
min(end, other_end) - start):
counts[x] += 1
nbases_overlapping += sum([1 for x in counts if x > 0])
infile.close()
return nexons, nexons_overlapping, nbases, nbases_overlapping
def getExonLocations(filename):
'''return a list of exon locations as Bed entries
from a file contain a one ensembl gene ID per line
'''
fh = IOTools.openFile(filename, "r")
ensembl_ids = []
for line in fh:
ensembl_ids.append(line.strip())
fh.close()
dbhandle = sqlite3.connect(PARAMS["annotations_database"])
cc = dbhandle.cursor()
gene_ids = []
n_ids = 0
for ID in ensembl_ids:
gene_ids.append('gene_id="%s"' % ID)
n_ids += 1
statement = "select contig,start,end from geneset_cds_gtf where " + \
" OR ".join(gene_ids)
cc.execute(statement)
region_list = []
n_regions = 0
for result in cc:
b = Bed.Bed()
b.contig, b.start, b.end = result
region_list.append(b)
n_regions += 1
cc.close()
E.info("Retrieved exon locations for %i genes. Got %i regions" %
(n_ids, n_regions))
return(region_list)
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if not argv:
argv = sys.argv
# setup command line parser
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option(
"-g", "--gtf-file", dest="filename_gtf", type="string",
help="filename with gene models in gtf format [%default]")
parser.add_option(
"-m", "--filename-mismapped", dest="filename_mismapped", type="string",
help="output bam file for mismapped reads [%default]")
parser.add_option(
"-j", "--junctions-bed-file", dest="filename_junctions", type="string",
help="bam file with reads mapped across junctions [%default]")
parser.add_option(
"-r", "--filename-regions", dest="filename_regions", type="string",
help="filename with regions to remove in bed format [%default]")
parser.add_option(
"-t", "--transcripts-gtf-file", dest="filename_transcriptome",
type="string",
help="bam file with reads mapped against transcripts [%default]")
parser.add_option(
"-p", "--map-tsv-file", dest="filename_map", type="string",
help="filename mapping transcript numbers (used by "
"--filename-transciptome) to transcript names "
"(used by --filename-gtf) [%default]")
parser.add_option(
"-s", "--filename-stats", dest="filename_stats", type="string",
help="filename to output stats to [%default]")
parser.add_option(
"-o", "--colour",
dest="colour_mismatches", action="store_true",
help="mismatches will use colour differences (CM tag) [%default]")
parser.add_option(
"-i", "--ignore-mismatches",
dest="ignore_mismatches", action="store_true",
help="ignore mismatches [%default]")
parser.add_option(
"-c", "--remove-contigs", dest="remove_contigs", type="string",
help="','-separated list of contigs to remove [%default]")
parser.add_option(
"-f", "--force-output", dest="force", action="store_true",
help="force overwriting of existing files [%default]")
parser.add_option("-u", "--unique", dest="unique", action="store_true",
help="remove reads not matching uniquely [%default]")
parser.add_option("--output-sam", dest="output_sam", action="store_true",
help="output in sam format [%default]")
parser.set_defaults(
filename_gtf=None,
filename_mismapped=None,
filename_junctions=None,
filename_transcriptome=None,
filename_map=None,
remove_contigs=None,
force=False,
unique=False,
colour_mismatches=False,
ignore_mismatches=False,
output_sam=False,
filename_table=None,
)
# add common options (-h/--help, ...) and parse command line
(options, args) = E.start(parser, argv=argv)
if len(args) != 1:
raise ValueError("please supply one bam file")
bamfile_genome = args[0]
genome_samfile = pysam.AlignmentFile(bamfile_genome, "rb")
if options.remove_contigs:
options.remove_contigs = options.remove_contigs.split(",")
if options.filename_map:
E.info("reading map")
id_map = IOTools.read_map(
IOTools.open_file(options.filename_map), has_header=True)
id_map = dict([(y, x) for x, y in id_map.items()])
else:
id_map = None
transcripts = {}
if options.filename_gtf:
E.info("indexing geneset")
mapped, missed = 0, 0
for gtf in GTF.transcript_iterator(
GTF.iterator(IOTools.open_file(options.filename_gtf))):
gtf.sort(key=lambda x: x.start)
transcript_id = gtf[0].transcript_id
if id_map:
try:
transcript_id = id_map[transcript_id]
mapped += 1
except KeyError:
missed += 1
continue
transcripts[transcript_id] = gtf
E.info("read %i transcripts from geneset (%i mapped, %i missed)" %
(len(transcripts), mapped, missed))
regions_to_remove = None
if options.filename_regions:
E.info("indexing regions")
regions_to_remove = IndexedGenome.Simple()
for bed in Bed.iterator(IOTools.open_file(options.filename_regions)):
regions_to_remove.add(bed.contig, bed.start, bed.end)
E.info("read %i regions" % len(regions_to_remove))
if options.filename_transcriptome:
transcripts_samfile = pysam.AlignmentFile(options.filename_transcriptome,
"rb")
else:
transcripts_samfile = None
if options.output_sam:
output_samfile = pysam.AlignmentFile("-", "wh", template=genome_samfile)
else:
output_samfile = pysam.AlignmentFile("-", "wb", template=genome_samfile)
if options.filename_mismapped:
if not options.force and os.path.exists(options.filename_mismapped):
raise IOError("output file %s already exists" %
options.filename_mismapped)
output_mismapped = pysam.AlignmentFile(options.filename_mismapped,
"wb",
template=genome_samfile)
else:
output_mismapped = None
if options.filename_junctions:
junctions_samfile = pysam.AlignmentFile(options.filename_junctions,
"rb")
else:
junctions_samfile = None
c = bams2bam_filter(genome_samfile,
output_samfile,
output_mismapped,
transcripts_samfile,
junctions_samfile,
transcripts,
regions=regions_to_remove,
unique=options.unique,
remove_contigs=options.remove_contigs,
colour_mismatches=options.colour_mismatches,
ignore_mismatches=options.ignore_mismatches,
ignore_transcripts=transcripts_samfile is None,
ignore_junctions=junctions_samfile is None)
if options.filename_stats:
outf = IOTools.open_file(options.filename_stats, "w")
outf.write("category\tcounts\n%s\n" % c.asTable())
outf.close()
if options.filename_transcriptome:
transcripts_samfile.close()
genome_samfile.close()
output_samfile.close()
if output_mismapped:
output_mismapped.close()
# write footer and output benchmark information.
E.stop()
def main(argv=sys.argv):
# setup command line parser
parser = E.OptionParser(
version="%prog version: $Id$", usage=globals()["__doc__"])
parser.add_option("-n", "--new-instance", dest="new_instance",
action="store_true",
help="create a new IGV instance [%default]")
parser.add_option("-s", "--session", dest="session",
type="string",
help="load session before creating plots "
"[%default]")
parser.add_option("-d", "--snapshot-dir", dest="snapshotdir",
type="string",
help="directory to save snapshots in [%default]")
parser.add_option("-f", "--format", dest="format", type="choice",
choices=("png", "eps", "svg"),
help="output file format [%default]")
parser.add_option("-o", "--host", dest="host", type="string",
help="host that IGV is running on [%default]")
parser.add_option("-p", "--port", dest="port", type="int",
help="port that IGV listens at [%default]")
parser.add_option("-e", "--extend", dest="extend", type="int",
help="extend each interval by a number of bases "
"[%default]")
parser.add_option("-x", "--expand", dest="expand", type="float",
help="expand each region by a certain factor "
"[%default]")
parser.add_option("--session-only", dest="session_only",
action="store_true",
help="plot session after opening, "
"ignore intervals "
"[%default]")
parser.add_option("--keep", dest="keep_open",
action="store_true",
help="keep a newly created IGV session open "
"[%default]")
parser.set_defaults(
command="igv.sh",
host='127.0.0.1',
port=61111,
snapshotdir=os.getcwd(),
extend=0,
format="png",
expand=1.0,
session=None,
session_only=False,
keep_open=False,
)
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
igv_process = None
if options.new_instance:
E.info("starting new IGV process")
igv_process = IGV.startIGV(command=options.command,
port=options.port)
E.info("new IGV process started")
E.info("connection to process on %s:%s" % (options.host, options.port))
E.info("saving images in %s" % options.snapshotdir)
igv = IGV.IGV(host=options.host,
port=options.port,
snapshot_dir=os.path.abspath(options.snapshotdir))
if options.session:
E.info('loading session from %s' % options.session)
igv.load(options.session)
E.info('loaded session')
if options.session_only:
E.info('plotting session only ignoring any intervals')
fn = "%s.%s" % (os.path.basename(options.session), options.format)
E.info("writing snapshot to '%s'" %
os.path.join(options.snapshotdir, fn))
igv.save(fn)
else:
c = E.Counter()
for bed in Bed.iterator(options.stdin):
c.input += 1
# IGV can not deal with white-space in filenames
name = re.sub("\s", "_", bed.name)
E.info("going to %s:%i-%i for %s" %
(bed.contig, bed.start, bed.end, name))
start, end = bed.start, bed.end
extend = options.extend
if options.expand:
d = end - start
extend = max(extend, (options.expand * d - d) // 2)
start -= extend
end += extend
igv.go("%s:%i-%i" % (bed.contig, start, end))
fn = "%s.%s" % (name, options.format)
E.info("writing snapshot to '%s'" % fn)
igv.save(fn)
c.snapshots += 1
E.info(c)
if igv_process is not None and not options.keep_open:
E.info('shutting down IGV')
igv_process.send_signal(signal.SIGKILL)
E.Stop()
def main(argv=None):
if argv is None:
argv = sys.argv
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option("-g",
"--genome-file",
dest="genome_file",
type="string",
help="filename with genome [default=%default].")
parser.add_option("-a",
"--aggregate-by",
dest="aggregate",
type="choice",
choices=("name", "contig", "track", "none"),
help="aggregate counts by feature [default=%default].")
parser.add_option("-p",
"--add-percent",
dest="add_percent",
action="store_true",
help="add percentages [default=%default].")
parser.set_defaults(
genome_file=None,
aggregate="none",
add_percent=False,
)
(options, args) = E.Start(parser, argv)
# get files
if options.genome_file:
fasta = IndexedFasta.IndexedFasta(options.genome_file)
else:
if options.add_percent:
raise ValueError("--add-percent option requires --genome-file")
fasta = None
if options.add_percent and not options.aggregate == "contig":
raise NotImplementedError(
"--add-percent option requires --aggregate=contig")
counts = collections.defaultdict(Counter)
total = Counter()
output_totals = True
if options.aggregate == "track":
keyf = lambda x: x.track
elif options.aggregate == "name":
keyf = lambda x: x.name
elif options.aggregate == "contig":
keyf = lambda x: x.contig
else:
keyf = lambda x: "all"
output_totals = False
for bed in Bed.iterator(options.stdin):
counts[keyf(bed)].add(bed)
total.add(bed)
outf = options.stdout
key = "track"
if options.add_percent:
outf.write("%s\t%s\n" % (key, "\t".join(Counter.headers_percent)))
else:
outf.write("%s\t%s\n" % (key, "\t".join(Counter.headers)))
total_bases = 0
for key, count in sorted(counts.items()):
if options.add_percent:
total_bases += fasta.getLength(key)
count.setSize(fasta.getLength(key))
outf.write("%s\t%s\n" % (key, str(count)))
if output_totals:
if options.add_percent:
count.setSize(total_bases)
outf.write("%s\t%s\n" % ("total", str(total)))
E.Stop()
def formatProbeFragments(probe_fragments_bed, outfile):
# Create strings for output collisions
probe_collisions = ""
exclus_collisions = ""
with IOTools.openFile(outfile, "w") as outf:
# dictionaries for collisions per chr
chr_probe = {}
chr_exclus = {}
for bed_digest in Bed.iterator(IOTools.openFile(probe_fragments_bed)):
# chromosome needs to specify only number (remove chr)
chromosome = re.sub('chr', '', bed_digest.contig)
out_array = []
out_array.append(formatNameCompliance(bed_digest["name"]))
out_array.append(str(chromosome))
out_array.append(str(bed_digest.start))
out_array.append(str(bed_digest.end))
out_array.append(str(chromosome))
out_array.append(str(bed_digest.start-1000))
out_array.append(str(bed_digest.end+1000))
out_array.append("1")
out_array.append("A")
outf.write("\t".join(out_array) + "\n")
# Calculate collisions, all coordinates assumed in BED format
# It needs to be done per chr
# chr_probe -> probe_ranges -> probe_range
# chr_exclus -> exclus_ranges -> exclus_range
# Check if chromosome key already exists in one of the
# dictionaries
# (ranges introduced before on that chromosome
if bed_digest.contig in chr_probe:
# If it exists, get the array of probe ranges
# and exclusion ranges already stored
probe_ranges = chr_probe[bed_digest.contig]
exclus_ranges = chr_exclus[bed_digest.contig]
# If it doesn't create the arrays
else:
probe_ranges = []
exclus_ranges = []
# Create a range for probes and exclusion fragments
probe_range = []
exclus_range = []
probe_range.append(bed_digest.start)
probe_range.append(bed_digest.end)
probe_ranges.append(probe_range)
exclus_range.append(bed_digest.start-1000)
exclus_range.append(bed_digest.end+1000)
exclus_ranges.append(exclus_range)
# Substitute the ranges back to the corresponding chr in the
# dictionary
chr_probe[bed_digest.contig] = probe_ranges
chr_exclus[bed_digest.contig] = exclus_ranges
for chr in chr_probe:
probe_ranges = chr_probe[chr]
exclus_ranges = chr_exclus[chr]
probe_intersection = set.intersection(*(set(range(start, finish)) for start, finish in probe_ranges))
exclus_intersection = set.intersection(*(set(range(start, finish)) for start, finish in exclus_ranges))
if(len(probe_intersection) != 0):
probe_collisions += "Probe collision " +str(chr)
probe_collisions += " " +str(min(probe_intersection))
probe_collisions += " " +str(max(probe_intersection))
probe_collisions += "\n"
if(len(exclus_intersection) != 0):
exclus_collisions += "Exclusion collision " +str(chr)
exclus_collisions += " " +str(min(exclus_intersection))
exclus_collisions += " " +str(max(exclus_intersection))
exclus_collisions += "\n"
return (probe_collisions, exclus_collisions)
def main(argv=sys.argv):
parser = E.OptionParser(version="%prog version: $Id: bed2bed.py 2861 2010-02-23 17:36:32Z andreas $",
usage=globals()["__doc__"])
# IMS: new method: extend intervals by set amount
parser.add_option("-m", "--method", dest="methods", type="choice", action="append",
choices=("merge", "filter-genome", "bins",
"block", "sanitize-genome", "shift", "extend"),
help="method to apply [default=%default]")
parser.add_option("--num-bins", dest="num_bins", type="int",
help="number of bins into which to merge (used for method `bins) [default=%default]")
parser.add_option("--bin-edges", dest="bin_edges", type="string",
help="bin_edges for binning method [default=%default]")
parser.add_option("--binning-method", dest="binning_method", type="choice",
choices=(
"equal-bases", "equal-intervals", "equal-range"),
help="method used for binning (used for method `bins` if no bin_edges is given) [default=%default]")
parser.add_option("--merge-distance", dest="merge_distance", type="int",
help="distance in bases over which to merge that are not directly adjacent [default=%default]")
parser.add_option("--merge-min-intervals", dest="merge_min_intervals", type="int",
help="only output merged intervals that are build from at least x intervals [default=%default]")
parser.add_option("--merge-by-name", dest="merge_by_name", action="store_true",
help="only merge intervals with the same name [default=%default]")
parser.add_option("--remove-inconsistent", dest="remove_inconsistent", action="store_true",
help="when merging, do not output intervals where the names of overlapping intervals "
"do not match [default=%default]")
parser.add_option("--offset", dest="offset", type="int",
help="offset for shifting intervals [default=%default]")
parser.add_option("-g", "--genome-file", dest="genome_file", type="string",
help="filename with genome.")
parser.add_option("-b", "--bam-file", dest="bam_file", type="string",
help="bam-formatted filename with genome.")
parser.set_defaults(methods=[],
merge_distance=0,
binning_method="equal-bases",
merge_by_name=False,
genome_file=None,
bam_file=None,
num_bins=5,
merge_min_intervals=1,
bin_edges=None,
offset=10000,
test=None,
extend_distance=1000,
remove_inconsistent=False)
(options, args) = E.Start(parser, add_pipe_options=True)
contigs = None
# Why provide full indexed genome, when a tsv of contig sizes would do?
if options.genome_file:
genome_fasta = IndexedFasta.IndexedFasta(options.genome_file)
contigs = genome_fasta.getContigSizes()
if options.bam_file:
samfile = pysam.Samfile(options.bam_file)
contigs = dict(zip(samfile.references, samfile.lengths))
processor = Bed.iterator(options.stdin)
for method in options.methods:
if method == "filter-genome":
if not contigs:
raise ValueError("please supply contig sizes")
processor = filterGenome(processor, contigs)
elif method == "sanitize-genome":
if not contigs:
raise ValueError("please supply contig sizes")
processor = sanitizeGenome(processor, contigs)
elif method == "merge":
processor = merge(processor,
options.merge_distance,
by_name=options.merge_by_name,
min_intervals=options.merge_min_intervals,
remove_inconsistent=options.remove_inconsistent)
elif method == "bins":
if options.bin_edges:
bin_edges = map(float, options.bin_edges.split(","))
# IMS: check bin edges are valid
if not(len(bin_edges) == options.num_bins + 1):
raise ValueError(
"Number of bin edge must be one more than number of bins")
else:
bin_edges = None
processor, bin_edges = Bed.binIntervals(processor,
num_bins=options.num_bins,
method=options.binning_method,
bin_edges=bin_edges)
E.info("# split bed: bin_edges=%s" % (str(bin_edges)))
elif method == "block":
processor = Bed.blocked_iterator(processor)
elif method == "shift":
# IMS: test that contig sizes are availible
if not contigs:
raise ValueError("please supply genome file")
processor = shiftIntervals(
processor, contigs, offset=options.offset)
# IMS: new method: extend intervals by set amount
elif method == "extend":
if not contigs:
raise ValueError("please supply genome file")
processor = extendInterval(processor, contigs, options.offset)
noutput = 0
for bed in processor:
options.stdout.write(str(bed) + "\n")
noutput += 1
E.info("noutput=%i" % (noutput))
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
# setup command line parser
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option("-m","--method", dest="method", type="choice",
choices=["ave_dist","min_dist","corr"],
default="min_dist",
help="Method for calcuating similarity between profiles")
parser.add_option("-s", "--spread", dest="spread", type="int",
default=10,
help="Amount to spread each tag by")
parser.add_option("-k", "--keep-dist", dest="keep_dist",
action="store_true",
help="Keep the distribution of tag depths")
parser.add_option("-r", "--rands", dest="rands",
default=100,
help="Number of randomisations to use for calculating"
" mean and stdev of distance")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
profile1_file, profile2_file = args
profile1_file = pysam.AlignmentFile(profile1_file)
if profile2_file.endswith("bed") or profile2_file.endswith("bed.gz"):
profile2_file = Bed.readAndIndex(profile2_file, with_values=True)
profile2_counter = bed_counter
else:
profile2_file = pysam.AlignmentFile(profile2_file)
profile2_counter = iCLIP.count_intervals
if options.method=="min_dist":
distance_func = iCLIP.findMinDistance
elif options.method=="ave_dist":
distance_func = iCLIP.calcAverageDistance
else:
def distance_func(profile1,profile2):
return iCLIP.corr_profile(profile1,profile2, options.spread, profile2_ready=True)
for exon in GTF.iterator(options.stdin):
if exon.feature != "exon":
continue
contig = exon.contig
strand = exon.strand
transcript_id = exon.transcript_id
start = exon.start
end = exon.end
profile1 = iCLIP.count_intervals(profile1_file,
[(start, end)],
contig=contig,
strand=strand)
profile2 = profile2_counter(profile2_file,
[(start, end)],
contig=contig,
strand=strand)
if profile1.sum() == 0 or profile2.sum() == 0:
z = "NA"
distance = "NA"
options.stdout.write(
"%(contig)s\t%(start)i\t%(end)i\t%(transcript_id)s\t%(strand)s\t%(distance)s\t%(z)s\n" % locals())
continue
if options.method=="corr":
profile2 = iCLIP.spread(profile2, options.spread)
distance = distance_func(profile1, profile2)
rands = iCLIP.rand_apply(profile=profile1,
exon=exon,
n=options.rands,
func=distance_func,
keep_dist=options.keep_dist,
profile2=profile2)
z = (distance - rands.mean())/rands.std()
options.stdout.write(
"%(contig)s\t%(start)i\t%(end)i\t%(transcript_id)s\t%(strand)s\t%(distance).3f\t%(z).2f\n" % locals())
# write footer and output benchmark information.
E.Stop()
def loadIntervalsFromBed(bedfile, track, outfile,
bamfiles, offsets):
'''load intervals from :term:`bed` formatted files into database.
Re-evaluate the intervals by counting reads within
the interval. In contrast to the initial pipeline, the
genome is not binned. In particular, the meaning of the
columns in the table changes to:
nProbes: number of reads in interval
PeakCenter: position with maximum number of reads in interval
AvgVal: average coverage within interval
'''
tmpfile = P.getTempFile(".")
headers = ("AvgVal", "DisttoStart", "GeneList", "Length", "PeakCenter", "PeakVal", "Position",
"interval_id", "nCpGs", "nGenes", "nPeaks", "nProbes", "nPromoters", "contig", "start", "end")
tmpfile.write("\t".join(headers) + "\n")
avgval, contig, disttostart, end, genelist, length, peakcenter, peakval, position, start, interval_id, ncpgs, ngenes, npeaks, nprobes, npromoters = \
0, "", 0, 0, "", 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
mlength = int(PARAMS["calling_merge_min_interval_length"])
c = E.Counter()
# count tags
for bed in Bed.iterator(IOTools.openFile(infile, "r")):
c.input += 1
if "name" not in bed:
bed.name = c.input
# remove very short intervals
if bed.end - bed.start < mlength:
c.skipped_length += 1
continue
if replicates:
npeaks, peakcenter, length, avgval, peakval, nprobes = \
PipelineChipseq.countPeaks(
bed.contig, bed.start, bed.end,
samfiles, offsets)
# nreads can be 0 if the intervals overlap only slightly
# and due to the binning, no reads are actually in the
# overlap region. However, most of these intervals should
# be small and have already be deleted via the
# merge_min_interval_length cutoff. do not output
# intervals without reads.
if nprobes == 0:
c.skipped_reads += 1
else:
npeaks, peakcenter, length, avgval, peakval, nprobes = (
1,
bed.start +
(bed.end - bed.start) // 2,
bed.end - bed.start,
1,
1,
1)
c.output += 1
tmpfile.write("\t".join(map(
str,
(avgval, disttostart, genelist, length,
peakcenter, peakval, position, bed.name,
ncpgs, ngenes, npeaks, nprobes, npromoters,
bed.contig, bed.start, bed.end))) + "\n")
if c.output == 0:
E.warn("%s - no intervals")
tmpfile.close()
tmpfilename = tmpfile.name
tablename = "%s_intervals" % track.asTable()
statement = '''
cgat csv2db %(csv2db_options)s
--allow-empty-file
--add-index=interval_id
--table=%(tablename)s
< %(tmpfilename)s
> %(outfile)s
'''
P.run()
os.unlink(tmpfile.name)
E.info("%s\n" % str(c))
def main(argv=None):
if argv is None:
argv = sys.argv
parser = E.OptionParser(
version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option(
"-g", "--genome-file", dest="genome_file", type="string",
help="filename with genome [default=%default].")
parser.add_option(
"-a", "--aggregate-by", dest="aggregate", type="choice",
choices=("name", "contig", "track", "none"),
help="aggregate counts by feature [default=%default].")
parser.add_option(
"-p", "--add-percent", dest="add_percent", action="store_true",
help="add percentages [default=%default].")
parser.set_defaults(
genome_file=None,
aggregate="none",
add_percent=False,
)
(options, args) = E.Start(parser, argv)
# get files
if options.genome_file:
fasta = IndexedFasta.IndexedFasta(options.genome_file)
else:
if options.add_percent:
raise ValueError("--add-percent option requires --genome-file")
fasta = None
if options.add_percent and not options.aggregate == "contig":
raise NotImplementedError(
"--add-percent option requires --aggregate=contig")
counts = collections.defaultdict(Counter)
total = Counter()
output_totals = True
if options.aggregate == "track":
keyf = lambda x: x.track
elif options.aggregate == "name":
keyf = lambda x: x.name
elif options.aggregate == "contig":
keyf = lambda x: x.contig
else:
keyf = lambda x: "all"
output_totals = False
for bed in Bed.iterator(options.stdin):
counts[keyf(bed)].add(bed)
total.add(bed)
outf = options.stdout
key = "track"
if options.add_percent:
outf.write("%s\t%s\n" % (key, "\t".join(Counter.headers_percent)))
else:
outf.write("%s\t%s\n" % (key, "\t".join(Counter.headers)))
total_bases = 0
for key, count in sorted(counts.items()):
if options.add_percent:
total_bases += fasta.getLength(key)
count.setSize(fasta.getLength(key))
outf.write("%s\t%s\n" % (key, str(count)))
if output_totals:
if options.add_percent:
count.setSize(total_bases)
outf.write("%s\t%s\n" % ("total", str(total)))
E.Stop()
def main(argv=sys.argv):
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option("-a",
"--as-gtf",
dest="as_gtf",
action="store_true",
help="output as gtf.")
parser.add_option(
"-f",
"--id-format",
dest="id_format",
type="string",
help="format for numeric identifier if --as-gtf is set and "
"no name in bed file [%default].")
parser.set_defaults(as_gtf=False, id_format="%08i", test=None)
(options, args) = E.start(parser, add_pipe_options=True)
as_gtf = options.as_gtf
id_format = options.id_format
if as_gtf:
gff = GTF.Entry()
else:
gff = GTF.Entry()
gff.source = "bed"
gff.feature = "exon"
ninput, noutput, nskipped = 0, 0, 0
id = 0
for bed in Bed.iterator(options.stdin):
ninput += 1
gff.contig = bed.contig
gff.start = bed.start
gff.end = bed.end
if bed.fields and len(bed.fields) >= 3:
gff.strand = bed.fields[2]
else:
gff.strand = "."
if bed.fields and len(bed.fields) >= 2:
gff.score = bed.fields[1]
if as_gtf:
if bed.fields:
gff.gene_id = bed.fields[0]
gff.transcript_id = bed.fields[0]
else:
id += 1
gff.gene_id = id_format % id
gff.transcript_id = id_format % id
else:
if bed.fields:
gff.source = bed.fields[0]
options.stdout.write(str(gff) + "\n")
noutput += 1
E.info("ninput=%i, noutput=%i, nskipped=%i" % (ninput, noutput, nskipped))
E.stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if not argv:
argv = sys.argv
# setup command line parser
parser = E.OptionParser(version="%prog version: $Id: cgat_script_template.py 2871 2010-03-03 10:20:44Z andreas $",
usage=globals()["__doc__"])
parser.add_option("-i", "--infiles", dest="infiles", type="string",
metavar="bed",
action="append", help="supply list of bed files")
parser.set_defaults(infiles=[])
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
options.infiles.extend(args)
if len(options.infiles) == 0:
raise ValueError('please provide at least 1 bed file')
E.info("concatenating bed files")
# concatenate the list of files
tmp = tempfile.NamedTemporaryFile(delete=False)
tmp_merge = tempfile.NamedTemporaryFile(delete=False)
infs = options.infiles
for inf in infs:
for bed in Bed.iterator(IOTools.openFile(inf)):
tmp.write("%s\n" % bed)
tmp.close()
E.info("merging bed entries")
# merge the bed entries in the file
name = tmp.name
tmp_bed = pybedtools.BedTool(name)
tmp_bed.merge().saveas(tmp_merge.name)
tmp_merge.close()
E.info("indexing bed entries")
# index the bed entries
merged = IndexedGenome.Simple()
for bed in Bed.iterator(IOTools.openFile(tmp_merge.name)):
merged.add(bed.contig, bed.start, bed.end)
counts = collections.defaultdict(int)
# list of samples
samples = options.infiles
E.info("counting no. samples overlapping each interval")
for sample in samples:
found = set()
for bed in Bed.iterator(IOTools.openFile(sample)):
if merged.contains(bed.contig, bed.start, bed.end):
key = [bed.contig] + \
[x for x in merged.get(bed.contig, bed.start, bed.end)]
key = (key[0], key[1][0], key[1][1])
if key in found:
continue
found.add(key)
# tuple of interval description as key - (contig, start, end)
counts[key] += 1
# open outfile
options.stdout.write("contig\tstart\tend\tcount\n")
E.info("outputting result")
for interval, count in counts.iteritems():
options.stdout.write(
"\t".join(map(str, interval)) + "\t" + str(count) + "\n")
# write footer and output benchmark information.
E.Stop()
def __init__(self, filename):
self.mIndices = Bed.readAndIndex(IOTools.openFile(filename, "r"),
per_track=True)
def main(argv=None):
if argv is None:
argv = sys.argv
parser = E.OptionParser(
version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option("-g", "--genome-file", dest="genome_file", type="string",
help="filename with genomic sequence to retrieve "
"sequences from.")
parser.add_option("-m", "--masker", dest="masker", type="choice",
choices=("dust", "dustmasker", "softmask", "none"),
help="apply masker to mask output sequences "
"[%default].")
parser.add_option("--output-mode", dest="output_mode", type="choice",
choices=("intervals", "leftright", "segments"),
help="what to output. "
"'intervals' generates a single sequence for "
"each bed interval. 'leftright' generates two "
"sequences, one in each direction, for each bed "
"interval. 'segments' can be used to output "
"sequence from bed12 files so that sequence only covers "
"the segements [%default]")
parser.add_option("--min-sequence-length", dest="min_length", type="int",
help="require a minimum sequence length [%default]")
parser.add_option("--max-sequence-length", dest="max_length", type="int",
help="require a maximum sequence length [%default]")
parser.add_option(
"--extend-at", dest="extend_at", type="choice",
choices=("none", "3", "5", "both", "3only", "5only"),
help="extend at 3', 5' or both or no ends. If 3only or 5only "
"are set, only the added sequence is returned [default=%default]")
parser.add_option(
"--extend-by", dest="extend_by", type="int",
help="extend by # bases [default=%default]")
parser.add_option(
"--use-strand", dest="ignore_strand",
action="store_false",
help="use strand information and return reverse complement "
"on intervals located on the negative strand. "
"[default=%default]")
parser.set_defaults(
genome_file=None,
masker=None,
output_mode="intervals",
min_length=0,
max_length=0,
extend_at=None,
extend_by=100,
ignore_strand=True,
)
(options, args) = E.Start(parser)
if options.genome_file:
fasta = IndexedFasta.IndexedFasta(options.genome_file)
contigs = fasta.getContigSizes()
fasta.setConverter(IndexedFasta.getConverter("zero-both-open"))
counter = E.Counter()
ids, seqs = [], []
E.info("collecting sequences")
for bed in Bed.setName(Bed.iterator(options.stdin)):
counter.input += 1
lcontig = fasta.getLength(bed.contig)
if options.ignore_strand:
strand = "+"
else:
strand = bed.strand
if options.output_mode == "segments" and bed.columns == 12:
ids.append("%s %s:%i..%i (%s) %s %s" %
(bed.name, bed.contig, bed.start, bed.end, strand,
bed["blockSizes"], bed["blockStarts"]))
seg_seqs = [fasta.getSequence(bed.contig, strand, start, end)
for start, end in bed.toIntervals()]
seqs.append("".join(seg_seqs))
elif (options.output_mode == "intervals" or
options.output_mode == "segments"):
ids.append("%s %s:%i..%i (%s)" %
(bed.name, bed.contig, bed.start, bed.end, strand))
seqs.append(
fasta.getSequence(bed.contig, strand, bed.start, bed.end))
elif options.output_mode == "leftright":
l = bed.end - bed.start
start, end = max(0, bed.start - l), bed.end - l
ids.append("%s_l %s:%i..%i (%s)" %
(bed.name, bed.contig, start, end, strand))
seqs.append(fasta.getSequence(bed.contig, strand, start, end))
start, end = bed.start + l, min(lcontig, bed.end + l)
ids.append("%s_r %s:%i..%i (%s)" %
(bed.name, bed.contig, start, end, strand))
seqs.append(fasta.getSequence(bed.contig, strand, start, end))
E.info("collected %i sequences" % len(seqs))
masked = Masker.maskSequences(seqs, options.masker)
options.stdout.write(
"\n".join([">%s\n%s" % (x, y) for x, y in zip(ids, masked)]) + "\n")
E.info("masked %i sequences" % len(seqs))
counter.output = len(seqs)
E.info("%s" % counter)
E.Stop()
def main(argv=sys.argv):
# setup command line parser
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option("-m",
"--method",
dest="method",
type="choice",
choices=("igv", ),
help="method to create plots with [%default]")
parser.add_option("-d",
"--snapshot-dir",
dest="snapshotdir",
type="string",
help="directory to save snapshots in [%default]")
parser.add_option("-f",
"--format",
dest="format",
type="choice",
choices=("png", "eps", "svg"),
help="output file format [%default]")
parser.add_option("-o",
"--host",
dest="host",
type="string",
help="host that IGV is running on [%default]")
parser.add_option("-p",
"--port",
dest="port",
type="int",
help="port that IGV listens at [%default]")
parser.add_option(
"-e",
"--extend",
dest="extend",
type="int",
help="extend each interval by a number of bases [%default]")
parser.add_option("-x",
"--expand",
dest="expand",
type="float",
help="expand each region by a certain factor [%default]")
parser.set_defaults(
method="igv",
host='127.0.0.1',
port=61111,
snapshotdir=os.getcwd(),
extend=0,
format="png",
expand=1.0,
)
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
E.info("connection to session on %s:%s" % (options.host, options.port))
E.info("saving images in %s" % options.snapshotdir)
igv = IGV.IGV(host=options.host,
port=options.port,
snapshot_dir=os.path.abspath(options.snapshotdir))
c = E.Counter()
for bed in Bed.iterator(options.stdin):
c.input += 1
# IGV can not deal with white-space in filenames
name = re.sub("\s", "_", bed.name)
E.info("going to %s:%i-%i for %s" %
(bed.contig, bed.start, bed.end, name))
start, end = bed.start, bed.end
extend = options.extend
if options.expand:
d = end - start
extend = max(extend, (options.expand * d - d) // 2)
start -= extend
end += extend
igv.go("%s:%i-%i" % (bed.contig, start, end))
fn = "%s.%s" % (name, options.format)
E.info("writing snapshot to '%s'" % fn)
igv.save(fn)
c.snapshots += 1
E.info(c)
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv == None: argv = sys.argv
parser = E.OptionParser(
version=
"%prog version: $Id: bed2annotator2tsv.py 2885 2010-04-07 08:46:50Z andreas $",
usage=globals()["__doc__"])
parser.add_option("-g",
"--genome-file",
dest="genome_file",
type="string",
help="filename with genome.")
parser.add_option("-f",
"--features",
dest="features",
type="string",
help="feature to collect [default=None].")
parser.add_option("-i",
"--files",
dest="files",
action="append",
help="use multiple annotations [default=None].")
parser.add_option(
"-a",
"--annotations",
dest="annotations",
type="string",
help=
"aggregate name for annotations if only single file is provided from STDIN [default=None]."
)
parser.add_option(
"--input-filename-map",
dest="input_filename_map",
type="string",
help="filename with a map of gene_ids to categories [default=None].")
parser.add_option("-l",
"--max-length",
dest="max_length",
type="string",
help="maximum segment length [default=None].")
parser.add_option(
"-m",
"--merge",
dest="merge",
action="store_true",
help="merge overlapping bed segments [default=%default].")
parser.add_option("-s",
"--section",
dest="section",
type="choice",
choices=("segments", "annotations", "workspace"),
help="annotator section [default=None].")
parser.add_option(
"--subset",
dest="subsets",
type="string",
action="append",
help=
"add filenames to delimit subsets within the gff files. The syntax is filename.gff,label,filename.ids [default=None]."
)
parser.set_defaults(
genome_file=None,
feature=None,
remove_random=True,
section="segments",
annotations="annotations",
max_length=100000,
files=[],
subsets=[],
input_filename_map=None,
merge=False,
)
(options, args) = E.Start(parser)
options.files += args
if len(options.files) == 0: options.files.append("-")
options.files = list(
itertools.chain(*[re.split("[,; ]+", x) for x in options.files]))
if options.subsets:
subsets = collections.defaultdict(list)
for s in options.subsets:
filename_gff, label, filename_ids = s.split(",")
subsets[filename_gff].append((label, filename_ids))
options.subsets = subsets
if options.genome_file:
fasta = IndexedFasta.IndexedFasta(options.genome_file)
else:
fasta = None
if options.section == "segments":
prefix = "##Segs"
elif options.section == "annotations":
prefix = "##Id"
elif options.section == "workspace":
prefix = "##Work"
else:
raise ValueError("unknown section %s" % options.section)
if options.max_length:
max_length = options.max_length
else:
max_length = 0
ninput, ntracks, ncontigs, nsegments, ndiscarded = 0, 0, 0, 0, 0
if options.section in ("annotations"):
contigs = set()
it = itertools.groupby(Bed.iterator(options.stdin),
key=lambda x: x.track["name"])
map_track2segments = {}
for track, beds in it:
ntracks += 1
map_track2segments[track] = []
first_segment = nsegments
beds = list(beds)
if options.merge: beds = Bed.merge(beds)
for bed in beds:
contig, start, end = bed.contig, bed.start, bed.end
if options.remove_random and "random" in contig: continue
if max_length > 0 and end - start > max_length:
ndiscarded += 1
continue
contigs.add(contig)
map_track2segments[track].append(nsegments)
options.stdout.write("%s\t%i\t%s\t(%i,%i)\n" %
(prefix, nsegments, contig, start, end))
nsegments += 1
options.stdout.write("##Ann\t%s\t%s\n" % (track, "\t".join(
["%i" % x for x in range(first_segment, nsegments)])))
E.info("track %s: annotated with %i segments" %
(track, nsegments - first_segment))
ncontigs = len(contigs)
E.info(
"ninput=%i, ntracks=%i, ncontigs=%i, nsegments=%i, ndiscarded=%i" %
(ninput, ntracks, ncontigs, nsegments, ndiscarded))
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if not argv:
argv = sys.argv
# setup command line parser
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option("-m", "--min-overlap", dest="min_overlap",
type="float",
help="minimum overlap [%default]")
parser.add_option("-a", "--bam-file", dest="filename_bam",
metavar="bam", type="string",
help="bam-file to use (required) [%default]")
parser.add_option("-b", "--bed-file", dest="filename_bed",
metavar="bed", type="string",
help="bed-file to use (required) [%default]")
parser.add_option(
"-s", "--sort-bed", dest="sort_bed",
action="store_true",
help="sort the bed file by chromosomal location before "
"processing. "
"[%default]")
parser.add_option(
"--assume-sorted", dest="sort_bed",
action="store_false",
help="assume that the bed-file is sorted by chromosomal location. "
"[%default]")
parser.add_option(
"--split-intervals", dest="split_intervals",
action="store_true",
help="treat split BAM intervals, for example spliced intervals, "
"as separate intervals. Note that a single alignment might be "
"counted several times as a result. "
"[%default]")
parser.set_defaults(
min_overlap=0.5,
filename_bam=None,
filename_bed=None,
sort_bed=True,
split_intervals=False,
)
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
filename_bam = options.filename_bam
filename_bed = options.filename_bed
if filename_bam is None and filename_bed is None:
if len(args) != 2:
raise ValueError(
"please supply a bam and a bed file or two bed-files.")
filename_bam, filename_bed = args
if filename_bed is None:
raise ValueError("please supply a bed file to compare to.")
if filename_bam is None:
raise ValueError("please supply a bam file to compare with.")
E.info("intersecting the two files")
min_overlap = options.min_overlap
options.stdout.write("category\talignments\n")
# get number of columns of reference bed file
for bed in Bed.iterator(IOTools.openFile(filename_bed)):
ncolumns_bed = bed.columns
break
E.info("assuming %s is bed%i format" % (filename_bed, ncolumns_bed))
if ncolumns_bed < 4:
raise ValueError("please supply a name attribute in the bed file")
# get information about
if filename_bam.endswith(".bam"):
format = "-abam"
samfile = pysam.Samfile(filename_bam, "rb")
total = samfile.mapped
# latest bedtools uses bed12 format when bam is input
ncolumns_bam = 12
# count per read
sort_key = lambda x: x.name
else:
format = "-a"
total = IOTools.getNumLines(filename_bam)
# get bed format
ncolumns_bam = 0
for bed in Bed.iterator(IOTools.openFile(filename_bam)):
ncolumns_bam = bed.columns
break
if ncolumns_bam > 0:
E.info("assuming %s is bed%i fomat" % (filename_bam, ncolumns_bam))
if ncolumns_bam == 3:
# count per interval
sort_key = lambda x: (x.contig, x.start, x.end)
else:
# count per interval category
sort_key = lambda x: x.name
# use fields for bam/bed file (regions to count with)
data_fields = [
"contig", "start", "end", "name",
"score", "strand", "thickstart", "thickend", "rgb",
"blockcount", "blockstarts", "blockends"][:ncolumns_bam]
# add fields for second bed (regions to count in)
data_fields.extend([
"contig2", "start2", "end2", "name2",
"score2", "strand2", "thickstart2", "thickend2", "rgb2",
"blockcount2", "blockstarts2", "blockends2"][:ncolumns_bed])
# add bases overlap
data_fields.append("bases_overlap")
data = collections.namedtuple("data", data_fields)
options.stdout.write("total\t%i\n" % total)
if total == 0:
E.warn("no data in %s" % filename_bam)
return
# SNS: sorting optional, off by default
if options.sort_bed:
bedcmd = "<( zcat %s | sort -k1,1 -k2,2n)" % filename_bed
else:
bedcmd = filename_bed
if options.split_intervals:
split = "-split"
else:
split = ""
# IMS: newer versions of intersectBed have a very high memory
# requirement unless passed sorted bed files.
statement = """bedtools intersect %(format)s %(filename_bam)s
-b %(bedcmd)s
%(split)s
-sorted -bed -wo -f %(min_overlap)f""" % locals()
E.info("starting counting process: %s" % statement)
proc = E.run(statement,
return_popen=True,
stdout=subprocess.PIPE)
E.info("counting")
counts_per_alignment = collections.defaultdict(int)
take_columns = len(data._fields)
def iterate(infile):
for line in infile:
if not line.strip():
continue
yield data._make(line[:-1].split()[:take_columns])
for read, overlaps in itertools.groupby(
iterate(IOTools.force_str(proc.stdout)), key=sort_key):
annotations = [x.name2 for x in overlaps]
for anno in annotations:
counts_per_alignment[anno] += 1
for key, counts in sorted(counts_per_alignment.items()):
options.stdout.write("%s\t%i\n" % (key, counts))
# write footer and output benchmark information.
E.Stop()
def buildIndex(self, filename):
return Bed.readAndIndex(IOTools.openFile(filename, "r"))
def aggregateWindowsTagCounts(infiles, outfile, regex="(.*)\..*"):
'''aggregate output from several ``bedtools coverage`` results.
``bedtools coverage`` outputs the following columns for a bed4
file::
1 Contig
2 Start
3 Stop
4 Name
5 The number of features in A that overlapped (by at least one
base pair) the B interval.
6 The number of bases in B that had non-zero coverage from features in A.
7 The length of the entry in B.
8 The fraction of bases in B that had non-zero coverage from
features in A.
This method autodetects the number of columns in the :term:`infiles`
and selects:
* bed4: use column 5
* bed6: use column 7
* bed12: use column 13
Arguments
---------
infiles : list
Input filenames with the output from ``bedtools coverage``
outfile : string
Output filename in :term:`tsv` format.
regex : string
Regular expression used to extract the track name from the
filename. The default removes any suffix.
'''
# get bed format
bed_columns = Bed.getNumColumns(infiles[0])
# +1 as awk is 1-based
column = bed_columns - 4 + 1
src = " ".join([
"""<( zcat %s |
awk '{printf("%%s:%%i-%%i\\t%%i\\n", $1,$2,$3,$%s );}')""" %
(x, column) for x in infiles
])
tmpfile = P.get_temp_filename(".")
statement = '''paste %(src)s > %(tmpfile)s'''
P.run(statement)
# build track names
tracks = [
re.search(regex, os.path.basename(x)).groups()[0] for x in infiles
]
outf = IOTools.open_file(outfile, "w")
outf.write("interval_id\t%s\n" % "\t".join(tracks))
# filter for uniqueness - keys with the same value as the
# previous line will be ignored.
last_gene = None
c = E.Counter()
for line in open(tmpfile, "r"):
c.input += 1
data = line[:-1].split("\t")
genes = list(set([data[x] for x in range(0, len(data), 2)]))
values = [int(data[x]) for x in range(1, len(data), 2)]
assert len(genes) == 1, \
"paste command failed, wrong number of genes per line: '%s'" % line
if genes[0] == last_gene:
c.duplicates += 1
continue
c.output += 1
outf.write("%s\t%s\n" % (genes[0], "\t".join(map(str, values))))
last_gene = genes[0]
outf.close()
os.unlink(tmpfile)
E.info("aggregateWindowsTagCounts: %s" % c)
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if not argv:
argv = sys.argv
# setup command line parser
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option("-m",
"--min-overlap",
dest="min_overlap",
type="float",
help="minimum overlap [%default]")
parser.add_option("-a",
"--bam-file",
dest="filename_bam",
metavar="bam",
type="string",
help="bam-file to use (required) [%default]")
parser.add_option("-b",
"--bed-file",
dest="filename_bed",
metavar="bed",
type="string",
help="bed-file to use (required) [%default]")
parser.add_option("-s",
"--sort-bed",
dest="sort_bed",
action="store_true",
help="sort the bed file by chromosomal location before "
"processing. "
"[%default]")
parser.add_option(
"--assume-sorted",
dest="sort_bed",
action="store_false",
help="assume that the bed-file is sorted by chromosomal location. "
"[%default]")
parser.add_option(
"--split-intervals",
dest="split_intervals",
action="store_true",
help="treat split BAM intervals, for example spliced intervals, "
"as separate intervals. Note that a single alignment might be "
"counted several times as a result. "
"[%default]")
parser.set_defaults(
min_overlap=0.5,
filename_bam=None,
filename_bed=None,
sort_bed=True,
split_intervals=False,
)
# add common options (-h/--help, ...) and parse command line
(options, args) = E.start(parser, argv=argv)
filename_bam = options.filename_bam
filename_bed = options.filename_bed
if filename_bam is None and filename_bed is None:
if len(args) != 2:
raise ValueError(
"please supply a bam and a bed file or two bed-files.")
filename_bam, filename_bed = args
if filename_bed is None:
raise ValueError("please supply a bed file to compare to.")
if filename_bam is None:
raise ValueError("please supply a bam file to compare with.")
E.info("intersecting the two files")
min_overlap = options.min_overlap
options.stdout.write("category\talignments\n")
# get number of columns of reference bed file
for bed in Bed.iterator(IOTools.open_file(filename_bed)):
ncolumns_bed = bed.columns
break
E.info("assuming %s is bed%i format" % (filename_bed, ncolumns_bed))
if ncolumns_bed < 4:
raise ValueError("please supply a name attribute in the bed file")
# get information about
if filename_bam.endswith(".bam"):
format = "-abam"
samfile = pysam.AlignmentFile(filename_bam, "rb")
total = samfile.mapped
# latest bedtools uses bed12 format when bam is input
ncolumns_bam = 12
# count per read
sort_key = lambda x: x.name
else:
format = "-a"
total = IOTools.get_num_lines(filename_bam)
# get bed format
ncolumns_bam = 0
for bed in Bed.iterator(IOTools.open_file(filename_bam)):
ncolumns_bam = bed.columns
break
if ncolumns_bam > 0:
E.info("assuming %s is bed%i fomat" % (filename_bam, ncolumns_bam))
if ncolumns_bam == 3:
# count per interval
sort_key = lambda x: (x.contig, x.start, x.end)
else:
# count per interval category
sort_key = lambda x: x.name
# use fields for bam/bed file (regions to count with)
data_fields = [
"contig", "start", "end", "name", "score", "strand", "thickstart",
"thickend", "rgb", "blockcount", "blockstarts", "blockends"
][:ncolumns_bam]
# add fields for second bed (regions to count in)
data_fields.extend([
"contig2", "start2", "end2", "name2", "score2", "strand2",
"thickstart2", "thickend2", "rgb2", "blockcount2", "blockstarts2",
"blockends2"
][:ncolumns_bed])
# add bases overlap
data_fields.append("bases_overlap")
data = collections.namedtuple("data", data_fields)
options.stdout.write("total\t%i\n" % total)
if total == 0:
E.warn("no data in %s" % filename_bam)
return
# SNS: sorting optional, off by default
if options.sort_bed:
bedcmd = "<( gunzip < %s | sort -k1,1 -k2,2n)" % filename_bed
else:
bedcmd = filename_bed
if options.split_intervals:
split = "-split"
else:
split = ""
# IMS: newer versions of intersectBed have a very high memory
# requirement unless passed sorted bed files.
statement = """bedtools intersect %(format)s %(filename_bam)s
-b %(bedcmd)s
%(split)s
-sorted -bed -wo -f %(min_overlap)f""" % locals()
E.info("starting counting process: %s" % statement)
proc = E.run(statement, return_popen=True, stdout=subprocess.PIPE)
E.info("counting")
counts_per_alignment = collections.defaultdict(int)
take_columns = len(data._fields)
def iterate(infile):
for line in infile:
if not line.strip():
continue
yield data._make(line[:-1].split()[:take_columns])
for read, overlaps in itertools.groupby(iterate(
IOTools.force_str(proc.stdout)),
key=sort_key):
annotations = [x.name2 for x in overlaps]
for anno in annotations:
counts_per_alignment[anno] += 1
for key, counts in sorted(counts_per_alignment.items()):
options.stdout.write("%s\t%i\n" % (key, counts))
# write footer and output benchmark information.
E.stop()
def __init__(self, filename):
self.mIndices = Bed.readAndIndex(IOTools.openFile(filename, "r"),
per_track=True)
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if not argv:
argv = sys.argv
# setup command line parser
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option(
"-g", "--gtf-file", dest="filename_gtf", type="string",
help="filename with gene models in gtf format [%default]")
parser.add_option(
"-m", "--filename-mismapped", dest="filename_mismapped", type="string",
help="output bam file for mismapped reads [%default]")
parser.add_option(
"-j", "--junctions-bed-file", dest="filename_junctions", type="string",
help="bam file with reads mapped across junctions [%default]")
parser.add_option(
"-r", "--filename-regions", dest="filename_regions", type="string",
help="filename with regions to remove in bed format [%default]")
parser.add_option(
"-t", "--transcripts-gtf-file", dest="filename_transcriptome",
type="string",
help="bam file with reads mapped against transcripts [%default]")
parser.add_option(
"-p", "--map-tsv-file", dest="filename_map", type="string",
help="filename mapping transcript numbers (used by "
"--filename-transciptome) to transcript names "
"(used by --filename-gtf) [%default]")
parser.add_option(
"-s", "--filename-stats", dest="filename_stats", type="string",
help="filename to output stats to [%default]")
parser.add_option(
"-o", "--colour",
dest="colour_mismatches", action="store_true",
help="mismatches will use colour differences (CM tag) [%default]")
parser.add_option(
"-i", "--ignore-mismatches",
dest="ignore_mismatches", action="store_true",
help="ignore mismatches [%default]")
parser.add_option(
"-c", "--remove-contigs", dest="remove_contigs", type="string",
help="','-separated list of contigs to remove [%default]")
parser.add_option(
"-f", "--force-output", dest="force", action="store_true",
help="force overwriting of existing files [%default]")
parser.add_option("-u", "--unique", dest="unique", action="store_true",
help="remove reads not matching uniquely [%default]")
parser.add_option("--output-sam", dest="output_sam", action="store_true",
help="output in sam format [%default]")
parser.set_defaults(
filename_gtf=None,
filename_mismapped=None,
filename_junctions=None,
filename_transcriptome=None,
filename_map=None,
remove_contigs=None,
force=False,
unique=False,
colour_mismatches=False,
ignore_mismatches=False,
output_sam=False,
filename_table=None,
)
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
if len(args) != 1:
raise ValueError("please supply one bam file")
bamfile_genome = args[0]
genome_samfile = pysam.Samfile(bamfile_genome, "rb")
if options.remove_contigs:
options.remove_contigs = options.remove_contigs.split(",")
if options.filename_map:
E.info("reading map")
id_map = IOTools.readMap(
IOTools.openFile(options.filename_map), has_header=True)
id_map = dict([(y, x) for x, y in id_map.iteritems()])
else:
id_map = None
transcripts = {}
if options.filename_gtf:
E.info("indexing geneset")
mapped, missed = 0, 0
for gtf in GTF.transcript_iterator(
GTF.iterator(IOTools.openFile(options.filename_gtf))):
gtf.sort(key=lambda x: x.start)
transcript_id = gtf[0].transcript_id
if id_map:
try:
transcript_id = id_map[transcript_id]
mapped += 1
except KeyError:
missed += 1
continue
transcripts[transcript_id] = gtf
E.info("read %i transcripts from geneset (%i mapped, %i missed)" %
(len(transcripts), mapped, missed))
regions_to_remove = None
if options.filename_regions:
E.info("indexing regions")
regions_to_remove = IndexedGenome.Simple()
for bed in Bed.iterator(IOTools.openFile(options.filename_regions)):
regions_to_remove.add(bed.contig, bed.start, bed.end)
E.info("read %i regions" % len(regions_to_remove))
if options.filename_transcriptome:
transcripts_samfile = pysam.Samfile(options.filename_transcriptome,
"rb")
else:
transcripts_samfile = None
if options.output_sam:
output_samfile = pysam.Samfile("-", "wh", template=genome_samfile)
else:
output_samfile = pysam.Samfile("-", "wb", template=genome_samfile)
if options.filename_mismapped:
if not options.force and os.path.exists(options.filename_mismapped):
raise IOError("output file %s already exists" %
options.filename_mismapped)
output_mismapped = pysam.Samfile(options.filename_mismapped,
"wb",
template=genome_samfile)
else:
output_mismapped = None
if options.filename_junctions:
junctions_samfile = pysam.Samfile(options.filename_junctions,
"rb")
else:
junctions_samfile = None
c = _bams2bam.filter(genome_samfile,
output_samfile,
output_mismapped,
transcripts_samfile,
junctions_samfile,
transcripts,
regions=regions_to_remove,
unique=options.unique,
remove_contigs=options.remove_contigs,
colour_mismatches=options.colour_mismatches,
ignore_mismatches=options.ignore_mismatches,
ignore_transcripts=transcripts_samfile is None,
ignore_junctions=junctions_samfile is None)
if options.filename_stats:
outf = IOTools.openFile(options.filename_stats, "w")
outf.write("category\tcounts\n%s\n" % c.asTable())
outf.close()
if options.filename_transcriptome:
transcripts_samfile.close()
genome_samfile.close()
output_samfile.close()
if output_mismapped:
output_mismapped.close()
# write footer and output benchmark information.
E.Stop()
def buildIndex(self, filename):
return Bed.readAndIndex(IOTools.openFile(filename, "r"))
def main( argv = None ):
if argv == None: argv = sys.argv
parser = E.OptionParser( version = "%prog version: $Id: gtf2table.py 2888 2010-04-07 08:48:36Z andreas $", usage = globals()["__doc__"])
parser.add_option("-g", "--genome-file", dest="genome_file", type="string",
help="filename with genome [default=%default]." )
parser.add_option("-b", "--bam-file", dest="bam_files", type="string",
help="filename with read mapping information. Multiple files can be submitted in a comma-separated list [default=%default]." )
parser.add_option( "--control-bam-file", dest="control_bam_files", type="string",
help="filename with read mapping information for input/control. Multiple files can be submitted in a comma-separated list [default=%default]." )
parser.add_option( "--filename-format", dest="filename_format", type="choice",
choices=("bed", "gff", "gtf" ),
help="format of secondary stream [default=%default]." )
parser.add_option("-c", "--counter", dest="counters", type="choice", action="append",
choices=( "overlap",
"peaks",
"composition-na",
"composition-cpg",
"classifier-chipseq"),
help="select counters to apply [default=%default]." )
parser.add_option("-o", "--offset", dest="offsets", type="int", action="append",
help="tag offsets for tag counting - supply as many as there are bam-files [default=%default]." )
parser.add_option( "--control-offset", dest="control_offsets", type="int", action="append",
help="control tag offsets for tag counting - supply as many as there are bam-files [default=%default]." )
parser.add_option("-a", "--all-fields", dest="all_fields", action = "store_true",
help="output all fields in original bed file, by default only the first 4 are output [default=%default]." )
parser.add_option("--bed-headers", dest="bed_headers", type="string",
help="supply ',' separated list of headers for bed component [default=%default]." )
parser.add_option("-f", "--filename-gff", dest="filename_gff", type="string", action="append", metavar='bed',
help="filename with extra gff files. The order is important [default=%default]." )
parser.set_defaults(
genome_file = None,
counters = [],
bam_files = None,
offsets = [],
control_bam_files = None,
control_offsets = [],
all_fields = False,
filename_format = None,
bed_headers = "contig,start,end,name",
filename_gff = [],
)
(options, args) = E.Start( parser )
# get files
if options.genome_file:
fasta = IndexedFasta.IndexedFasta( options.genome_file )
else:
fasta = None
if options.bam_files:
bam_files = []
for bamfile in options.bam_files.split(","):
bam_files.append( pysam.Samfile(bamfile, "rb" ) )
else:
bam_files = None
if options.control_bam_files:
control_bam_files = []
for bamfile in options.control_bam_files.split(","):
control_bam_files.append( pysam.Samfile(bamfile, "rb" ) )
else:
control_bam_files = None
counters = []
for c in options.counters:
if c == "overlap":
counters.append( CounterOverlap( filename = options.filename_bed,
fasta=fasta,
options = options) )
elif c == "peaks":
counters.append( CounterPeaks( bam_files,
options.offsets,
control_bam_files,
options.control_offsets,
options = options ) )
elif c == "composition-na":
counters.append( CounterCompositionNucleotides( fasta=fasta,
options = options ))
elif c == "composition-cpg":
counters.append( CounterCompositionCpG( fasta=fasta,
options = options ) )
elif c == "classifier-chipseq":
counters.append( ClassifierChIPSeq( filename_gff = options.filename_gff,
fasta = fasta,
options = options,
prefix = None) )
options.stdout.write( "\t".join( [x.strip() for x in options.bed_headers.split(",") ] ) )
options.stdout.write( "\t" + "\t".join(
[ x.getHeader() for x in counters] ) + "\n" )
for bed in Bed.iterator(options.stdin):
for counter in counters:
counter.update(bed)
if options.all_fields:
options.stdout.write( str(bed) )
else:
options.stdout.write( "\t".join( (bed.contig,
str(bed.start),
str(bed.end),
bed.fields[0]) ) )
for counter in counters:
options.stdout.write("\t%s" % str(counter) )
options.stdout.write("\n")
E.Stop()
def main(argv=sys.argv):
parser = E.OptionParser(version="%prog version: $Id: bed2gff.py 2861 2010-02-23 17:36:32Z andreas $",
usage=globals()["__doc__"])
parser.add_option("-a", "--as-gtf", dest="as_gtf", action="store_true",
help="output as gtf.")
parser.add_option("-f", "--id-format", dest="id_format", type="string",
help="format for numeric identifier if --as-gtf is set and no name in bed file [%default].")
parser.set_defaults(as_gtf=False,
id_format="%08i",
test=None)
(options, args) = E.Start(parser, add_pipe_options=True)
as_gtf = options.as_gtf
id_format = options.id_format
if as_gtf:
gff = GTF.Entry()
else:
gff = GTF.Entry()
gff.source = "bed"
gff.feature = "exon"
ninput, noutput, nskipped = 0, 0, 0
id = 0
for bed in Bed.iterator(options.stdin):
ninput += 1
gff.contig = bed.contig
gff.start = bed.start
gff.end = bed.end
if bed.fields and len(bed.fields) >= 3:
gff.strand = bed.fields[2]
else:
gff.strand = "."
if bed.fields and len(bed.fields) >= 2:
gff.score = bed.fields[1]
if as_gtf:
if bed.fields:
gff.gene_id = bed.fields[0]
gff.transcript_id = bed.fields[0]
else:
id += 1
gff.gene_id = id_format % id
gff.transcript_id = id_format % id
else:
if bed.fields:
gff.source = bed.fields[0]
options.stdout.write(str(gff) + "\n")
noutput += 1
E.info("ninput=%i, noutput=%i, nskipped=%i" % (ninput, noutput, nskipped))
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
# setup command line parser
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option("-m",
"--method",
dest="method",
type="choice",
choices=["ave_dist", "min_dist", "corr"],
default="min_dist",
help="Method for calcuating similarity between profiles")
parser.add_option("-s",
"--spread",
dest="spread",
type="int",
default=10,
help="Amount to spread each tag by")
parser.add_option("-k",
"--keep-dist",
dest="keep_dist",
action="store_true",
help="Keep the distribution of tag depths")
parser.add_option("-r",
"--rands",
dest="rands",
default=100,
help="Number of randomisations to use for calculating"
" mean and stdev of distance")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
profile1_file, profile2_file = args
profile1_file = pysam.AlignmentFile(profile1_file)
if profile2_file.endswith("bed") or profile2_file.endswith("bed.gz"):
profile2_file = Bed.readAndIndex(profile2_file, with_values=True)
profile2_counter = bed_counter
else:
profile2_file = pysam.AlignmentFile(profile2_file)
profile2_counter = iCLIP.count_intervals
if options.method == "min_dist":
distance_func = iCLIP.findMinDistance
elif options.method == "ave_dist":
distance_func = iCLIP.calcAverageDistance
else:
def distance_func(profile1, profile2):
return iCLIP.corr_profile(profile1,
profile2,
options.spread,
profile2_ready=True)
for exon in GTF.iterator(options.stdin):
if exon.feature != "exon":
continue
contig = exon.contig
strand = exon.strand
transcript_id = exon.transcript_id
start = exon.start
end = exon.end
profile1 = iCLIP.count_intervals(profile1_file, [(start, end)],
contig=contig,
strand=strand)
profile2 = profile2_counter(profile2_file, [(start, end)],
contig=contig,
strand=strand)
if profile1.sum() == 0 or profile2.sum() == 0:
z = "NA"
distance = "NA"
options.stdout.write(
"%(contig)s\t%(start)i\t%(end)i\t%(transcript_id)s\t%(strand)s\t%(distance)s\t%(z)s\n"
% locals())
continue
if options.method == "corr":
profile2 = iCLIP.spread(profile2, options.spread)
distance = distance_func(profile1, profile2)
rands = iCLIP.rand_apply(profile=profile1,
exon=exon,
n=options.rands,
func=distance_func,
keep_dist=options.keep_dist,
profile2=profile2)
z = (distance - rands.mean()) / rands.std()
options.stdout.write(
"%(contig)s\t%(start)i\t%(end)i\t%(transcript_id)s\t%(strand)s\t%(distance).3f\t%(z).2f\n"
% locals())
# write footer and output benchmark information.
E.Stop()
def readSegments(infile,
indexed_workspace,
truncate=False,
format="gtf",
keep_ambiguous=False,
remove_overhangs=False):
"""read segments from infile.
segments not overlapping with indexed_workspace are removed.
If :attr: truncate is given, segments extending beyond the workspace
are truncated.
returns a list of segments for each contig in a dictionary
"""
counter = E.Counter()
segments = collections.defaultdict(list)
def addSegment(contig, start, end, counter):
if contig in indexed_workspace:
r = indexed_workspace[contig].find(start, end)
if not r:
counter.nskipped += 1
return
if len(r) > 1:
counter.nambiguous += 1
if not keep_ambiguous:
return
if truncate:
for x in r:
wstart, wend = x.start, x.end
rstart, rend = max(start, wstart), min(end, wend)
if start < wstart or end > wend:
counter.ntruncated += 1
segments[contig].append((rstart, rend))
counter.added += 1
elif remove_overhangs:
for x in r:
wstart, wend = x.start, x.end
rstart, rend = max(start, wstart), min(end, wend)
if start < wstart or end > wend:
counter.overhangs += 1
break
else:
segments[contig].append((start, end))
else:
segments[contig].append((start, end))
counter.added += 1
counter.nkept += 1
if format == "gtf":
gtf_iterator = GTF.flat_gene_iterator(GTF.iterator(infile))
for gene in gtf_iterator:
# get start and end ignoring introns
# contig, start, end = gene[0].contig, min( [x.start for x in gene] ), max( [x.end for x in gene] )
contig, coords = gene[0].contig, [(x.start, x.end) for x in gene]
counter.ninput += 1
for start, end in coords:
addSegment(contig, start, end, counter)
elif format == "bed":
bed_iterator = Bed.iterator(infile)
for bed in bed_iterator:
counter.ninput += 1
addSegment(bed.contig, bed.start, bed.end, counter)
E.info("read segments: %s" % str(counter))
return segments
