def coverage(args):
"""
%prog coverage fastafile ctg bedfile1 bedfile2 ..
Plot coverage from a set of BED files that contain the read mappings. The
paired read span will be converted to a new bedfile that contain the happy
mates. ctg is the chr/scf/ctg that you want to plot the histogram on.
If the bedfiles already contain the clone spans, turn on --spans.
"""
from jcvi.formats.bed import mates, bedpe
p = OptionParser(coverage.__doc__)
p.add_option("--ymax",
default=None,
type="int",
help="Limit ymax [default: %default]")
p.add_option(
"--spans",
default=False,
action="store_true",
help="BED files already contain clone spans [default: %default]")
opts, args, iopts = p.set_image_options(args, figsize="8x5")
if len(args) < 3:
sys.exit(not p.print_help())
fastafile, ctg = args[0:2]
bedfiles = args[2:]
sizes = Sizes(fastafile)
size = sizes.mapping[ctg]
plt.figure(1, (iopts.w, iopts.h))
ax = plt.gca()
bins = 100 # smooth the curve
lines = []
legends = []
not_covered = []
yy = .9
for bedfile, c in zip(bedfiles, "rgbcky"):
if not opts.spans:
pf = bedfile.rsplit(".", 1)[0]
matesfile = pf + ".mates"
if need_update(bedfile, matesfile):
matesfile, matesbedfile = mates([bedfile, "--lib"])
bedspanfile = pf + ".spans.bed"
if need_update(matesfile, bedspanfile):
bedpefile, bedspanfile = bedpe(
[bedfile, "--span", "--mates={0}".format(matesfile)])
bedfile = bedspanfile
bedsum = Bed(bedfile).sum(seqid=ctg)
notcoveredbases = size - bedsum
legend = bedfile.split(".")[0]
msg = "{0}: {1} bp not covered".format(legend,
thousands(notcoveredbases))
not_covered.append(msg)
print >> sys.stderr, msg
ax.text(.1, yy, msg, color=c, size=9, transform=ax.transAxes)
yy -= .08
cov = Coverage(bedfile, sizes.filename)
x, y = cov.get_plot_data(ctg, bins=bins)
line, = ax.plot(x, y, '-', color=c, lw=2, alpha=.5)
lines.append(line)
legends.append(legend)
leg = ax.legend(lines, legends, shadow=True, fancybox=True)
leg.get_frame().set_alpha(.5)
ylabel = "Average depth per {0}Kb".format(size / bins / 1000)
ax.set_xlim(0, size)
ax.set_ylim(0, opts.ymax)
ax.set_xlabel(ctg)
ax.set_ylabel(ylabel)
set_human_base_axis(ax)
figname = "{0}.{1}.pdf".format(fastafile, ctg)
savefig(figname, dpi=iopts.dpi, iopts=iopts)
def coverage(args):
"""
%prog coverage fastafile ctg bedfile1 bedfile2 ..
Plot coverage from a set of BED files that contain the read mappings. The
paired read span will be converted to a new bedfile that contain the happy
mates. ctg is the chr/scf/ctg that you want to plot the histogram on.
If the bedfiles already contain the clone spans, turn on --spans.
"""
from jcvi.formats.bed import mates, bedpe
p = OptionParser(coverage.__doc__)
p.add_option("--ymax", default=None, type="int",
help="Limit ymax [default: %default]")
p.add_option("--spans", default=False, action="store_true",
help="BED files already contain clone spans [default: %default]")
opts, args, iopts = p.set_image_options(args, figsize="8x5")
if len(args) < 3:
sys.exit(not p.print_help())
fastafile, ctg = args[0:2]
bedfiles = args[2:]
sizes = Sizes(fastafile)
size = sizes.mapping[ctg]
plt.figure(1, (iopts.w, iopts.h))
ax = plt.gca()
bins = 100 # smooth the curve
lines = []
legends = []
not_covered = []
yy = .9
for bedfile, c in zip(bedfiles, "rgbcky"):
if not opts.spans:
pf = bedfile.rsplit(".", 1)[0]
matesfile = pf + ".mates"
if need_update(bedfile, matesfile):
matesfile, matesbedfile = mates([bedfile, "--lib"])
bedspanfile = pf + ".spans.bed"
if need_update(matesfile, bedspanfile):
bedpefile, bedspanfile = bedpe([bedfile, "--span",
"--mates={0}".format(matesfile)])
bedfile = bedspanfile
bedsum = Bed(bedfile).sum(seqid=ctg)
notcoveredbases = size - bedsum
legend = bedfile.split(".")[0]
msg = "{0}: {1} bp not covered".format(legend, thousands(notcoveredbases))
not_covered.append(msg)
print >> sys.stderr, msg
ax.text(.1, yy, msg, color=c, size=9, transform=ax.transAxes)
yy -= .08
cov = Coverage(bedfile, sizes.filename)
x, y = cov.get_plot_data(ctg, bins=bins)
line, = ax.plot(x, y, '-', color=c, lw=2, alpha=.5)
lines.append(line)
legends.append(legend)
leg = ax.legend(lines, legends, shadow=True, fancybox=True)
leg.get_frame().set_alpha(.5)
ylabel = "Average depth per {0}Kb".format(size / bins / 1000)
ax.set_xlim(0, size)
ax.set_ylim(0, opts.ymax)
ax.set_xlabel(ctg)
ax.set_ylabel(ylabel)
set_human_base_axis(ax)
figname ="{0}.{1}.pdf".format(fastafile, ctg)
savefig(figname, dpi=iopts.dpi, iopts=iopts)