def summarizeMACSFDR(infiles, outfile):
'''compile table with peaks that would remain after filtering
by fdr.
'''
fdr_thresholds = numpy.arange(0, 1.05, 0.05)
outf = IOTools.openFile(outfile, "w")
outf.write("track\t%s\n" % "\t".join(map(str, fdr_thresholds)))
for infile in infiles:
called = []
track = P.snip(os.path.basename(infile), ".macs")
infilename = infile + "_peaks.xls.gz"
inf = IOTools.openFile(infilename)
peaks = list(WrapperMACS.iteratePeaks(inf))
for threshold in fdr_thresholds:
called.append(len([x for x in peaks if x.fdr <= threshold]))
outf.write("%s\t%s\n" % (track, "\t".join(map(str, called))))
outf.close()
def summarizeMACSFDR(infiles, outfile):
'''compile table with peaks that would remain after filtering
by fdr.
'''
fdr_thresholds = numpy.arange(0, 1.05, 0.05)
outf = IOTools.openFile(outfile, "w")
outf.write("track\t%s\n" % "\t".join(map(str, fdr_thresholds)))
for infile in infiles:
called = []
track = P.snip(os.path.basename(infile), ".macs")
infilename = infile + "_peaks.xls.gz"
inf = IOTools.openFile(infilename)
peaks = list(WrapperMACS.iteratePeaks(inf))
for threshold in fdr_thresholds:
called.append(len([x for x in peaks if x.fdr <= threshold]))
outf.write("%s\t%s\n" % (track, "\t".join(map(str, called))))
outf.close()
def loadMACS(infile, outfile, bamfile, tablename=None):
'''load MACS results in *tablename*
This method loads only positive peaks. It filters peaks by p-value,
q-value and fold change and loads the diagnostic data and
re-calculates peakcenter, peakval, ... using the supplied bamfile.
If *tablename* is not given, it will be :file:`<track>_intervals`
where track is derived from ``infile`` and assumed to end
in :file:`.macs`.
This method creates two optional additional files:
* if the file :file:`<track>_diag.xls` is present, load MACS
diagnostic data into the table :file:`<track>_macsdiag`.
* if the file :file:`<track>_model.r` is present, call R to
create a MACS peak-shift plot and save it as :file:`<track>_model.pdf`
in the :file:`export/MACS` directory.
This method creates :file:`<outfile>.tsv.gz` with the results
of the filtering.
'''
track = P.snip(os.path.basename(infile), ".macs")
folder = os.path.dirname(infile)
if len(folder) > 0:
infilename = folder + "/" + track + "_peaks.xls"
filename_diag = folder + "/" + track + "_diag.xls"
filename_r = folder + "/" + track + "_model.r"
filename_rlog = folder + "/" + track + ".r.log"
filename_pdf = track + "_model.pdf"
else:
infilename = track + "_peaks.xls"
filename_diag = track + "_diag.xls"
filename_r = track + "_model.r"
filename_rlog = track + ".r.log"
filename_pdf = track + "_model.pdf"
if not os.path.exists(infilename):
E.warn("could not find %s" % infilename)
P.touch(outfile)
return
# create plot by calling R
if os.path.exists(filename_r):
if len(folder) > 0:
statement = '''R --vanilla < %(filename_r)s > %(filename_rlog)s; mv %(filename_pdf)s %(folder)s/%(filename_pdf)s; '''
else:
statement = '''R --vanilla < %(filename_r)s > %(filename_rlog)s; '''
P.run()
# filter peaks
shift = getPeakShiftFromMacs(infile)
assert shift is not None, "could not determine peak shift from MACS file %s" % infile
E.info("%s: found peak shift of %i" % (track, shift))
samfiles = [pysam.Samfile(bamfile, "rb")]
offsets = [shift / 2]
outtemp = P.getTempFile(".")
tmpfilename = outtemp.name
outtemp.write("\t".join((
"interval_id",
"contig", "start", "end",
"npeaks", "peakcenter",
"length",
"avgval",
"peakval",
"nprobes",
"pvalue", "fold", "qvalue",
"macs_summit", "macs_nprobes",
)) + "\n")
id = 0
# get thresholds
max_qvalue = float(PARAMS["macs_max_qvalue"])
# min, as it is -10log10
min_pvalue = float(PARAMS["macs_min_pvalue"])
counter = E.Counter()
with IOTools.openFile(infilename, "r") as ins:
for peak in WrapperMACS.iteratePeaks(ins):
if peak.fdr > max_qvalue:
counter.removed_qvalue += 1
continue
elif peak.pvalue < min_pvalue:
counter.removed_pvalue += 1
continue
assert peak.start < peak.end
npeaks, peakcenter, length, avgval, peakval, nreads = countPeaks(
peak.contig, peak.start, peak.end, samfiles, offsets)
outtemp.write("\t".join(map(str, (
id, peak.contig, peak.start, peak.end,
npeaks, peakcenter, length, avgval, peakval, nreads,
peak.pvalue, peak.fold, peak.fdr,
peak.start + peak.summit - 1,
peak.tags))) + "\n")
id += 1
counter.output += 1
outtemp.close()
# output filtering summary
outf = IOTools.openFile("%s.tsv.gz" % outfile, "w")
outf.write("category\tcounts\n")
outf.write("%s\n" % counter.asTable())
outf.close()
E.info("%s filtering: %s" % (track, str(counter)))
if counter.output == 0:
E.warn("%s: no peaks found" % track)
# load data into table
if tablename is None:
tablename = "%s_macs_intervals" % track
statement = '''cgat csv2db %(csv2db_options)s
--allow-empty-file
--add-index=interval_id
--add-index=contig,start
--table=%(tablename)s
< %(tmpfilename)s > %(outfile)s '''
P.run()
os.unlink(tmpfilename)
# load diagnostic data
if os.path.exists(filename_diag):
tablename = "%s_macsdiag" % track
statement = '''
cat %(filename_diag)s
| sed "s/FC range.*/fc\\tnpeaks\\tp90\\tp80\\tp70\\tp60\\tp50\\tp40\\tp30\\tp20/"
| cgat csv2db %(csv2db_options)s
--map=fc:str
--table=%(tablename)s
>> %(outfile)s
'''
P.run()
def loadMACS(infile, outfile, bamfile, tablename=None):
'''load MACS results in *tablename*
This method loads only positive peaks. It filters peaks by p-value,
q-value and fold change and loads the diagnostic data and
re-calculates peakcenter, peakval, ... using the supplied bamfile.
If *tablename* is not given, it will be :file:`<track>_intervals`
where track is derived from ``infile`` and assumed to end
in :file:`.macs`.
This method creates two optional additional files:
* if the file :file:`<track>_diag.xls` is present, load MACS
diagnostic data into the table :file:`<track>_macsdiag`.
* if the file :file:`<track>_model.r` is present, call R to
create a MACS peak-shift plot and save it as :file:`<track>_model.pdf`
in the :file:`export/MACS` directory.
This method creates :file:`<outfile>.tsv.gz` with the results
of the filtering.
'''
track = P.snip(os.path.basename(infile), ".macs")
folder = os.path.dirname(infile)
if len(folder) > 0:
infilename = folder + "/" + track + "_peaks.xls"
filename_diag = folder + "/" + track + "_diag.xls"
filename_r = folder + "/" + track + "_model.r"
filename_rlog = folder + "/" + track + ".r.log"
filename_pdf = track + "_model.pdf"
else:
infilename = track + "_peaks.xls"
filename_diag = track + "_diag.xls"
filename_r = track + "_model.r"
filename_rlog = track + ".r.log"
filename_pdf = track + "_model.pdf"
if not os.path.exists(infilename):
E.warn("could not find %s" % infilename)
P.touch(outfile)
return
# create plot by calling R
if os.path.exists(filename_r):
if len(folder) > 0:
statement = '''R --vanilla < %(filename_r)s > %(filename_rlog)s; mv %(filename_pdf)s %(folder)s/%(filename_pdf)s; '''
else:
statement = '''R --vanilla < %(filename_r)s > %(filename_rlog)s; '''
P.run()
# filter peaks
shift = getPeakShiftFromMacs(infile)
assert shift is not None, "could not determine peak shift from MACS file %s" % infile
E.info("%s: found peak shift of %i" % (track, shift))
samfiles = [pysam.Samfile(bamfile, "rb")]
offsets = [shift / 2]
outtemp = P.getTempFile(".")
tmpfilename = outtemp.name
outtemp.write("\t".join((
"interval_id",
"contig", "start", "end",
"npeaks", "peakcenter",
"length",
"avgval",
"peakval",
"nprobes",
"pvalue", "fold", "qvalue",
"macs_summit", "macs_nprobes",
)) + "\n")
id = 0
# get thresholds
max_qvalue = float(PARAMS["macs_max_qvalue"])
# min, as it is -10log10
min_pvalue = float(PARAMS["macs_min_pvalue"])
counter = E.Counter()
with IOTools.openFile(infilename, "r") as ins:
for peak in WrapperMACS.iteratePeaks(ins):
if peak.fdr > max_qvalue:
counter.removed_qvalue += 1
continue
elif peak.pvalue < min_pvalue:
counter.removed_pvalue += 1
continue
assert peak.start < peak.end
npeaks, peakcenter, length, avgval, peakval, nreads = countPeaks(
peak.contig, peak.start, peak.end, samfiles, offsets)
outtemp.write("\t".join(map(str, (
id, peak.contig, peak.start, peak.end,
npeaks, peakcenter, length, avgval, peakval, nreads,
peak.pvalue, peak.fold, peak.fdr,
peak.start + peak.summit - 1,
peak.tags))) + "\n")
id += 1
counter.output += 1
outtemp.close()
# output filtering summary
outf = IOTools.openFile("%s.tsv.gz" % outfile, "w")
outf.write("category\tcounts\n")
outf.write("%s\n" % counter.asTable())
outf.close()
E.info("%s filtering: %s" % (track, str(counter)))
if counter.output == 0:
E.warn("%s: no peaks found" % track)
# load data into table
if tablename is None:
tablename = "%s_macs_intervals" % track
statement = '''cgat csv2db %(csv2db_options)s
--allow-empty-file
--add-index=interval_id
--add-index=contig,start
--table=%(tablename)s
< %(tmpfilename)s > %(outfile)s '''
P.run()
os.unlink(tmpfilename)
# load diagnostic data
if os.path.exists(filename_diag):
tablename = "%s_macsdiag" % track
statement = '''
cat %(filename_diag)s
| sed "s/FC range.*/fc\\tnpeaks\\tp90\\tp80\\tp70\\tp60\\tp50\\tp40\\tp30\\tp20/"
| cgat csv2db %(csv2db_options)s
--map=fc:str
--table=%(tablename)s
>> %(outfile)s
'''
P.run()
