def pomegranate(args):
"""
%prog cotton seqids karyotype.layout mcscan.out all.bed synteny.layout
Build a figure that calls graphics.karyotype to illustrate the high ploidy
of WGD history of pineapple genome. The script calls both graphics.karyotype
and graphic.synteny.
"""
p = OptionParser(pomegranate.__doc__)
opts, args, iopts = p.set_image_options(args, figsize="9x7")
if len(args) != 5:
sys.exit(not p.print_help())
seqidsfile, klayout, datafile, bedfile, slayout = args
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1])
Karyotype(fig, root, seqidsfile, klayout)
Synteny(fig, root, datafile, bedfile, slayout)
# legend showing the orientation of the genes
draw_gene_legend(root, 0.42, 0.52, 0.48)
labels = ((0.04, 0.96, "A"), (0.04, 0.52, "B"))
panel_labels(root, labels)
root.set_xlim(0, 1)
root.set_ylim(0, 1)
root.set_axis_off()
pf = "pomegranate-karyotype"
image_name = pf + "." + iopts.format
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
def oropetium(args):
"""
%prog oropetium mcscan.out all.bed layout switch.ids
Build a composite figure that calls graphis.synteny.
"""
p = OptionParser(oropetium.__doc__)
p.add_option("--extra", help="Extra features in BED format")
opts, args, iopts = p.set_image_options(args, figsize="9x6")
if len(args) != 4:
sys.exit(not p.print_help())
datafile, bedfile, slayout, switch = args
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1])
Synteny(
fig, root, datafile, bedfile, slayout, switch=switch, extra_features=opts.extra
)
# legend showing the orientation of the genes
draw_gene_legend(root, 0.4, 0.57, 0.74, text=True, repeat=True)
# On the left panel, make a species tree
fc = "lightslategrey"
coords = {}
xs, xp = 0.16, 0.03
coords["oropetium"] = (xs, 0.7)
coords["setaria"] = (xs, 0.6)
coords["sorghum"] = (xs, 0.5)
coords["rice"] = (xs, 0.4)
coords["brachypodium"] = (xs, 0.3)
xs -= xp
coords["Panicoideae"] = join_nodes(root, coords, "setaria", "sorghum", xs)
xs -= xp
coords["BEP"] = join_nodes(root, coords, "rice", "brachypodium", xs)
coords["PACMAD"] = join_nodes(root, coords, "oropetium", "Panicoideae", xs)
xs -= xp
coords["Poaceae"] = join_nodes(root, coords, "BEP", "PACMAD", xs)
# Names of the internal nodes
for tag in ("BEP", "Poaceae"):
nx, ny = coords[tag]
nx, ny = nx - 0.005, ny - 0.02
root.text(nx, ny, tag, rotation=90, ha="right", va="top", color=fc)
for tag in ("PACMAD",):
nx, ny = coords[tag]
nx, ny = nx - 0.005, ny + 0.02
root.text(nx, ny, tag, rotation=90, ha="right", va="bottom", color=fc)
root.set_xlim(0, 1)
root.set_ylim(0, 1)
root.set_axis_off()
pf = "oropetium"
image_name = pf + "." + iopts.format
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
def litchi(args):
"""
%prog litchi mcscan.out all.bed layout switch.ids
Build a composite figure that calls graphis.synteny.
"""
p = OptionParser(litchi.__doc__)
opts, args, iopts = p.set_image_options(args, figsize="9x6")
if len(args) != 4:
sys.exit(not p.print_help())
datafile, bedfile, slayout, switch = args
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1])
Synteny(fig, root, datafile, bedfile, slayout, switch=switch)
# legend showing the orientation of the genes
draw_gene_legend(root, .4, .7, .82)
# On the left panel, make a species tree
fc = 'lightslategrey'
coords = {}
xs, xp = .16, .03
coords["lychee"] = (xs, .37)
coords["clementine"] = (xs, .5)
coords["cacao"] = (xs, .6)
coords["strawberry"] = (xs, .7)
coords["grape"] = (xs, .8)
xs -= xp
coords["Sapindales"] = join_nodes(root, coords, "clementine", "lychee", xs)
xs -= xp
coords["Rosid-II"] = join_nodes(root, coords, "cacao", "Sapindales", xs)
xs -= xp
coords["Rosid"] = join_nodes(root, coords, "strawberry", "Rosid-II", xs)
xs -= xp
coords["crown"] = join_nodes(root,
coords,
"grape",
"Rosid",
xs,
circle=False)
# Names of the internal nodes
for tag in ("Rosid", "Rosid-II", "Sapindales"):
nx, ny = coords[tag]
nx, ny = nx - .01, ny - .02
root.text(nx, ny, tag, rotation=90, ha="right", va="top", color=fc)
root.set_xlim(0, 1)
root.set_ylim(0, 1)
root.set_axis_off()
pf = "litchi"
image_name = pf + "." + iopts.format
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
def utricularia(args):
from jcvi.graphics.synteny import main as synteny_main
p = OptionParser(synteny_main.__doc__)
p.add_option("--switch", help="Rename the seqid with two-column file")
opts, args, iopts = p.set_image_options(args, figsize="8x7")
if len(args) != 3:
sys.exit(not p.print_help())
datafile, bedfile, layoutfile = args
switch = opts.switch
pf = datafile.rsplit(".", 1)[0]
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1])
s = Synteny(fig,
root,
datafile,
bedfile,
layoutfile,
loc_label=False,
switch=switch)
light = "lightslategrey"
RoundRect(root, (0.02, 0.69), 0.96, 0.24, fill=False, lw=2, ec=light)
RoundRect(root, (0.02, 0.09), 0.96, 0.48, fill=False, lw=2, ec=light)
za, zb = s.layout[1].ratio, s.layout[-1].ratio # zoom level
if za != 1:
root.text(
0.96,
0.89,
"{}x zoom".format(za).replace(".0x", "x"),
color=light,
ha="right",
va="center",
size=14,
)
if zb != 1:
root.text(
0.96,
0.12,
"{}x zoom".format(zb).replace(".0x", "x"),
color=light,
ha="right",
va="center",
size=14,
)
# legend showing the orientation of the genes
draw_gene_legend(root, 0.22, 0.3, 0.64, text=True)
root.set_xlim(0, 1)
root.set_ylim(0, 1)
root.set_axis_off()
image_name = pf + "." + iopts.format
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
def draw_ploidy(fig, root, blocksfile, bedfile, blockslayout):
switchidsfile = "switch.ids"
Synteny(
fig,
root,
blocksfile,
bedfile,
blockslayout,
scalebar=True,
switch=switchidsfile,
)
# Legend showing the orientation of the genes
draw_gene_legend(root, 0.2, 0.3, 0.53)
# WGD labels
radius = 0.025
tau_color = "#bebada"
alpha_color = "#bc80bd"
label_color = "k"
pad = 0.05
for y in (0.74 + 1.5 * pad, 0.26 - 1.5 * pad):
TextCircle(
root,
0.25,
y,
r"$\alpha^{O}$",
radius=radius,
fc=alpha_color,
color=label_color,
fontweight="bold",
)
TextCircle(
root,
0.75,
y,
r"$\alpha^{O}$",
radius=radius,
fc=alpha_color,
color=label_color,
fontweight="bold",
)
for y in (0.74 + 3 * pad, 0.26 - 3 * pad):
TextCircle(root,
0.5,
y,
r"$\tau$",
radius=radius,
fc=tau_color,
color=label_color)
def amborella(args):
"""
%prog amborella seqids karyotype.layout mcscan.out all.bed synteny.layout
Build a composite figure that calls graphics.karyotype and graphics.synteny.
"""
p = OptionParser(amborella.__doc__)
p.add_option(
"--tree",
help="Display trees on the bottom of the figure [default: %default]")
p.add_option(
"--switch",
help="Rename the seqid with two-column file [default: %default]")
opts, args, iopts = p.set_image_options(args, figsize="8x7")
if len(args) != 5:
sys.exit(not p.print_help())
seqidsfile, klayout, datafile, bedfile, slayout = args
switch = opts.switch
tree = opts.tree
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1])
Karyotype(fig, root, seqidsfile, klayout)
Synteny(fig, root, datafile, bedfile, slayout, switch=switch, tree=tree)
# legend showing the orientation of the genes
draw_gene_legend(root, .5, .68, .5)
# annotate the WGD events
fc = 'lightslategrey'
x = .05
radius = .012
TextCircle(root, x, .86, '$\gamma$', radius=radius)
TextCircle(root, x, .95, '$\epsilon$', radius=radius)
root.plot([x, x], [.83, .9], ":", color=fc, lw=2)
pts = plot_cap((x, .95), np.radians(range(-70, 250)), .02)
x, y = zip(*pts)
root.plot(x, y, ":", color=fc, lw=2)
root.set_xlim(0, 1)
root.set_ylim(0, 1)
root.set_axis_off()
pf = "amborella"
image_name = pf + "." + iopts.format
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
def ploidy(args):
"""
%prog ploidy seqids karyotype.layout mcscan.out all.bed synteny.layout
Build a figure that calls graphics.karyotype to illustrate the high ploidy
of WGD history of pineapple genome. The script calls both graphics.karyotype
and graphic.synteny.
"""
p = OptionParser(ploidy.__doc__)
p.add_option("--switch", help="Rename the seqid with two-column file")
opts, args, iopts = p.set_image_options(args, figsize="9x7")
if len(args) != 5:
sys.exit(not p.print_help())
seqidsfile, klayout, datafile, bedfile, slayout = args
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1])
Karyotype(fig, root, seqidsfile, klayout)
Synteny(fig, root, datafile, bedfile, slayout, switch=opts.switch)
# legend showing the orientation of the genes
draw_gene_legend(root, .27, .37, .52)
# annotate the WGD events
fc = 'lightslategrey'
x = .09
radius = .012
TextCircle(root, x, .825, r'$\tau$', radius=radius, fc=fc)
TextCircle(root, x, .8, r'$\sigma$', radius=radius, fc=fc)
TextCircle(root, x, .72, r'$\rho$', radius=radius, fc=fc)
for ypos in (.825, .8, .72):
root.text(.12, ypos, r"$\times2$", color=fc, ha="center", va="center")
root.plot([x, x], [.85, .775], ":", color=fc, lw=2)
root.plot([x, x], [.75, .675], ":", color=fc, lw=2)
labels = ((.04, .96, 'A'), (.04, .54, 'B'))
panel_labels(root, labels)
root.set_xlim(0, 1)
root.set_ylim(0, 1)
root.set_axis_off()
pf = "pineapple-karyotype"
image_name = pf + "." + iopts.format
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
def cotton(args):
"""
%prog cotton seqids karyotype.layout mcscan.out all.bed synteny.layout
Build a composite figure that calls graphics.karyotype and graphic.synteny.
"""
p = OptionParser(cotton.__doc__)
p.add_option("--depthfile",
help="Use depth info in this file [default: %default]")
p.add_option(
"--switch",
help="Rename the seqid with two-column file [default: %default]")
opts, args, iopts = p.set_image_options(args, figsize="8x7")
if len(args) != 5:
sys.exit(p.print_help())
seqidsfile, klayout, datafile, bedfile, slayout = args
switch = opts.switch
depthfile = opts.depthfile
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1])
kt = Karyotype(fig, root, seqidsfile, klayout)
Synteny(fig, root, datafile, bedfile, slayout, switch=switch)
light = "lightslategrey"
# Show the dup depth along the cotton chromosomes
if depthfile:
ymin, ymax = .9, .95
root.text(.11, .96, "Cotton duplication level", color="gray", size=10)
root.plot([.1, .95], [ymin, ymin], color="gray")
root.text(.96, .9, "1x", color="gray", va="center")
root.plot([.1, .95], [ymax, ymax], color="gray")
root.text(.96, .95, "6x", color="gray", va="center")
fp = open(depthfile)
track = kt.tracks[0] # Cotton
depths = []
for row in fp:
a, b, depth = row.split()
depth = int(depth)
try:
p = track.get_coords(a)
depths.append((p, depth))
except KeyError:
pass
depths.sort(key=lambda x: (x[0], -x[1]))
xx, yy = zip(*depths)
yy = [ymin + .01 * (x - 1) for x in yy]
root.plot(xx, yy, "-", color=light)
# legend showing the orientation of the genes
draw_gene_legend(root, .5, .68, .5)
# Zoom
xpos = .835
ytop = .9
xmin, xmax = .18, .82
ymin, ymax = ytop, .55
lc = "k"
kwargs = dict(lw=3, color=lc, mec=lc, mfc="w", zorder=3)
root.plot((xpos, xpos), (ymax, .63), ":o", **kwargs)
root.plot((xpos, xmin), (ymax, ymin), ":o", **kwargs)
root.plot((xpos, xmax), (ymax, ymin), ":o", **kwargs)
RoundRect(root, (.06, .17), .92, .35, fill=False, lw=2, ec=light)
# Panels
root.text(.05, .95, "a", size=20, fontweight="bold")
root.text(.1, .45, "b", size=20, fontweight="bold")
root.set_xlim(0, 1)
root.set_ylim(0, 1)
root.set_axis_off()
pf = "cotton"
image_name = pf + "." + iopts.format
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
def expr(args):
"""
%prog expr block exp layout napus.bed
Plot a composite figure showing synteny and the expression level between
homeologs in two tissues - total 4 lists of values. block file contains the
gene pairs between AN and CN.
"""
from jcvi.graphics.base import red_purple as default_cm
p = OptionParser(expr.__doc__)
opts, args, iopts = p.set_image_options(args, figsize="8x5")
if len(args) != 4:
sys.exit(not p.print_help())
block, exp, layout, napusbed = args
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1])
s = Synteny(fig, root, block, napusbed, layout)
# Import the expression values
# Columns are: leaf-A, leaf-C, root-A, root-C
fp = open(exp)
data = {}
for row in fp:
gid, lf, rt = row.split()
lf, rt = float(lf), float(rt)
data[gid] = (lf, rt)
rA, rB = s.rr
gA = [x.accn for x in rA.genes]
gC = [x.accn for x in rB.genes]
A = [data.get(x, (0, 0)) for x in gA]
C = [data.get(x, (0, 0)) for x in gC]
A = np.array(A)
C = np.array(C)
A = np.transpose(A)
C = np.transpose(C)
d, h = .01, .1
lsg = "lightslategrey"
coords = s.gg # Coordinates of the genes
axes = []
for j, (y, gg) in enumerate(((.79, gA), (.24, gC))):
r = s.rr[j]
x = r.xstart
w = r.xend - r.xstart
ax = fig.add_axes([x, y, w, h])
axes.append(ax)
root.add_patch(
Rectangle((x - h, y - d),
w + h + d,
h + 2 * d,
fill=False,
ec=lsg,
lw=1))
root.text(x - d, y + 3 * h / 4, "root", ha="right", va="center")
root.text(x - d, y + h / 4, "leaf", ha="right", va="center")
ty = y - 2 * d if y > .5 else y + h + 2 * d
nrows = len(gg)
for i, g in enumerate(gg):
start, end = coords[(j, g)]
sx, sy = start
ex, ey = end
assert sy == ey
sy = sy + 2 * d if sy > .5 else sy - 2 * d
root.plot(((sx + ex) / 2, x + w * (i + .5) / nrows), (sy, ty),
lw=1,
ls=":",
color="k",
alpha=.2)
axA, axC = axes
p = axA.pcolormesh(A, cmap=default_cm)
p = axC.pcolormesh(C, cmap=default_cm)
axA.set_xlim(0, len(gA))
axC.set_xlim(0, len(gC))
x, y, w, h = .35, .1, .3, .05
ax_colorbar = fig.add_axes([x, y, w, h])
fig.colorbar(p, cax=ax_colorbar, orientation='horizontal')
root.text(x - d, y + h / 2, "RPKM", ha="right", va="center")
root.set_xlim(0, 1)
root.set_ylim(0, 1)
for x in (axA, axC, root):
x.set_axis_off()
image_name = "napusf4b." + iopts.format
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
def fig4(args):
"""
%prog fig4 layout data
Napus Figure 4A displays an example deleted region for quartet chromosomes,
showing read alignments from high GL and low GL lines.
"""
p = OptionParser(fig4.__doc__)
p.add_option("--gauge_step",
default=200000,
type="int",
help="Step size for the base scale")
opts, args, iopts = p.set_image_options(args, figsize="9x7")
if len(args) != 2:
sys.exit(not p.print_help())
layout, datadir = args
layout = F4ALayout(layout, datadir=datadir)
gs = opts.gauge_step
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1])
block, napusbed, slayout = "r28.txt", "all.bed", "r28.layout"
s = Synteny(fig, root, block, napusbed, slayout, chr_label=False)
synteny_exts = [(x.xstart, x.xend) for x in s.rr]
h = .1
order = "bzh,yudal".split(",")
labels = (r"\textit{B. napus} A$\mathsf{_n}$2",
r"\textit{B. rapa} A$\mathsf{_r}$2",
r"\textit{B. oleracea} C$\mathsf{_o}$2",
r"\textit{B. napus} C$\mathsf{_n}$2")
for t in layout:
xstart, xend = synteny_exts[2 * t.i]
canvas = [xstart, t.y, xend - xstart, h]
root.text(xstart - h,
t.y + h / 2,
labels[t.i],
ha="center",
va="center")
ch, ab = t.box_region.split(":")
a, b = ab.split("-")
vlines = [int(x) for x in (a, b)]
Coverage(fig,
root,
canvas,
t.seqid, (t.start, t.end),
datadir,
order=order,
gauge="top",
plot_chr_label=False,
gauge_step=gs,
palette="gray",
cap=40,
hlsuffix="regions.forhaibao",
vlines=vlines)
# Highlight GSL biosynthesis genes
a, b = (3, "Bra029311"), (5, "Bo2g161590")
for gid in (a, b):
start, end = s.gg[gid]
xstart, ystart = start
xend, yend = end
x = (xstart + xend) / 2
arrow = FancyArrowPatch(posA=(x, ystart - .04),
posB=(x, ystart - .005),
arrowstyle="fancy,head_width=6,head_length=8",
lw=3,
fc='k',
ec='k',
zorder=20)
root.add_patch(arrow)
root.set_xlim(0, 1)
root.set_ylim(0, 1)
root.set_axis_off()
image_name = "napus-fig4." + iopts.format
savefig(image_name, dpi=iopts.dpi, iopts=iopts)