def output_DFR(args):
from HiCmodule import JuicerMatrix
resolution = args.resolution
samples = []
samples.append(JuicerMatrix("RPM", args.control, resolution))
samples.append(JuicerMatrix("RPM", args.input, resolution))
smooth_median_filter = 3
EnrichMatrices = make3dmatrixRatio(samples, smooth_median_filter)
# import pdb; pdb.set_trace()
dfr = DirectionalFreqRatio(EnrichMatrices[0], resolution)
if (args.dfr_right == True):
array = dfr.getarrayplus()
elif (args.dfr_left == True):
array = dfr.getarrayminus()
else:
array = dfr.getarraydiff()
df = pd.DataFrame(array)
df.columns = ["DFR"]
df["chr"] = args.chr
df["start"] = np.arange(len(array)) * resolution
df["end"] = df["start"] + resolution
df = df.loc[:, ["chr", "start", "end", "DFR"]]
df.to_csv(args.output + ".bedGraph", sep="\t", header=False, index=False)
def main():
parser = argparse.ArgumentParser()
tp = lambda x: list(map(str, x.split(':')))
parser.add_argument("input",
help="<Input direcoty>:<label>",
type=tp,
nargs='*')
parser.add_argument("output", help="Output prefix", type=str)
parser.add_argument("chr", help="chromosome", type=str)
parser.add_argument("--log", help="logged count", action='store_true')
parser.add_argument("--type",
help="normalize type",
type=str,
default="KR")
parser.add_argument("-r",
"--resolution",
help="resolution",
type=int,
default=25000)
parser.add_argument("-s", "--start", help="start bp", type=int, default=0)
parser.add_argument("-e",
"--end",
help="end bp",
type=int,
default=1000000)
parser.add_argument("--vmax",
help="max value of color bar",
type=int,
default=50)
parser.add_argument("--vmin",
help="min value of color bar",
type=int,
default=0)
parser.add_argument("-d",
"--vizdistancemax",
help="max distance in heatmap",
type=int,
default=0)
parser.add_argument("--xsize",
help="xsize for figure",
type=int,
default=10)
parser.add_argument("--ysize",
help="ysize (* times of samples)",
type=int,
default=3)
args = parser.parse_args()
# print(args)
dirs = []
labels = []
for input in args.input:
dirs.append(input[0])
if (len(input) > 1):
labels.append(input[1])
else:
labels.append("")
chr = args.chr
resolution = args.resolution
type = args.type
figstart = args.start
figend = args.end
s = int(figstart / resolution)
e = int(figend / resolution)
vmax = args.vmax
vmin = args.vmin
if (args.log):
vmax = np.log1p(vmax)
vmin = np.log1p(vmin)
print(chr)
print(resolution)
samples = []
for dir in dirs:
# observed = dir + "/Matrix/intrachromosomal/" + str(resolution) + "/observed." + type + "." + chr + ".matrix.gz"
samples.append(JuicerMatrix("RPM", dir, resolution))
plt.subplot(1, 1, 1)
if (args.log):
m1 = samples[0].getlog()
m2 = samples[1].getlog()
else:
m1 = samples[0].getmatrix()
m2 = samples[1].getmatrix()
matrix = np.triu(m1) + np.tril(m2, k=-1)
if (labels[0] != "" and labels[1] != ""):
label = labels[0] + "-" + labels[1]
else:
label = ""
drawHeatmapSquare(plt,
matrix,
resolution,
figstart=figstart,
figend=figend,
vmax=vmax,
vmin=vmin,
label=label,
xticks=False)
plt.savefig(args.output + ".pdf")
def main():
parser = argparse.ArgumentParser()
tp = lambda x:list(map(str, x.split(':')))
parser.add_argument("input", help="<Input direcoty>:<label>", type=tp, nargs='*')
parser.add_argument("output", help="Output prefix", type=str)
parser.add_argument("chr", help="chromosome", type=str)
parser.add_argument("--log", help="logged count", action='store_true')
parser.add_argument("--type", help="normalize type", type=str, default="KR")
parser.add_argument("-r", "--resolution", help="resolution", type=int, default=25000)
parser.add_argument("-s", "--start", help="start bp", type=int, default=0)
parser.add_argument("-e", "--end", help="end bp", type=int, default=1000000)
parser.add_argument("--vmax", help="max value of color bar", type=int, default=50)
parser.add_argument("--vmin", help="min value of color bar", type=int, default=0)
parser.add_argument("--xsize", help="xsize for figure", type=int, default=3)
parser.add_argument("--ysize", help="ysize (* times of samples)", type=int, default=3)
args = parser.parse_args()
# print(args)
dirs = []
labels = []
for input in args.input:
dirs.append(input[0])
if (len(input) >1):
labels.append(input[1])
else:
labels.append("")
chr = args.chr
resolution = args.resolution
type = args.type
figstart = args.start
figend = args.end
s = int(figstart / resolution)
e = int(figend / resolution)
vmax = args.vmax
vmin = args.vmin
if (args.log):
vmax = np.log1p(vmax)
vmin = np.log1p(vmin)
print (chr)
print (resolution)
samples = []
for dir in dirs:
observed = dir + "/Matrix/intrachromosomal/" + str(resolution) + "/observed." + type + "." + chr + ".matrix.gz"
eigen = dir + "/eigen/" + str(resolution) + "/gd_eigen." + type + "." + chr + ".txt"
samples.append(JuicerMatrix("RPM", observed, resolution, eigenfile=eigen))
### Plot
nsample = len(samples)
plt.figure(figsize=(nsample*args.xsize/2, args.ysize*2))
for i, sample in enumerate(samples):
tadfile = dirs[i] + "/contact_domain/" + str(resolution) + "_blocks.bedpe"
print(tadfile)
tads = loadTADs(tadfile, chr[3:], start=figstart, end=figend)
loopfile = dirs[i] + "/loops/merged_loops.bedpe"
print(loopfile)
loops = loadloops(loopfile, chr[3:], start=figstart, end=figend)
# Hi-C Map
plt.subplot(2, len(samples)/2, i+1)
if (args.log):
drawHeatmapSquare(plt, sample.getlog(), resolution,
figstart=figstart, figend=figend,
tads=tads, loops=loops,
vmax=vmax, vmin=vmin,
label=labels[i], xticks=False)
else:
drawHeatmapSquare(plt, sample.getmatrix(), resolution,
figstart=figstart, figend=figend,
tads=tads, loops=loops,
vmax=vmax, vmin=vmin,
label=labels[i], xticks=False)
plt.tight_layout()
plt.savefig(args.output + ".pdf")
def main():
parser = argparse.ArgumentParser()
tp = lambda x: list(map(str, x.split(':')))
parser.add_argument("input",
help="<Input direcoty>:<label>",
type=tp,
nargs='*')
parser.add_argument("output", help="Output prefix", type=str)
parser.add_argument("chr", help="chromosome", type=str)
parser.add_argument("--type",
help="normalize type",
type=str,
default="KR")
parser.add_argument("--distance",
help="distance for DI",
type=int,
default=500000)
parser.add_argument("-r",
"--resolution",
help="resolution",
type=int,
default=25000)
parser.add_argument("-s", "--start", help="start bp", type=int, default=0)
parser.add_argument("-e",
"--end",
help="end bp",
type=int,
default=1000000)
parser.add_argument("--multi",
help="plot MultiInsulation Score",
action='store_true')
parser.add_argument("--compartment",
help="plot Compartment (eigen)",
action='store_true')
parser.add_argument("--di",
help="plot Directionaly Index",
action='store_true')
parser.add_argument("--dfr",
help="plot DirectionalFreqRatio",
action='store_true')
parser.add_argument("--dfr_right",
help="(with --dfr) plot DirectionalFreqRatio (Right)",
action='store_true')
parser.add_argument("--dfr_left",
help="(with --dfr) plot DirectionalFreqRatio (Left)",
action='store_true')
parser.add_argument("--vmax",
help="max value of color bar",
type=int,
default=50)
parser.add_argument("--vmin",
help="min value of color bar",
type=int,
default=0)
parser.add_argument("-d",
"--vizdistancemax",
help="max distance in heatmap",
type=int,
default=0)
parser.add_argument("--xsize",
help="xsize for figure",
type=int,
default=10)
# parser.add_argument("--ysize", help="ysize (* times of samples)", type=int, default=3)
args = parser.parse_args()
# print(args)
dirs = []
labels = []
for input in args.input:
dirs.append(input[0])
if (len(input) > 1):
labels.append(input[1])
else:
labels.append("")
chr = args.chr
resolution = args.resolution
type = args.type
figstart = args.start
figend = args.end
s = int(figstart / resolution)
e = int(figend / resolution)
length = figend - figstart
binnum = e - s
vmax = args.vmax
vmin = args.vmin
print("width: " + str(length) + ", " + str(binnum) + " bins.")
if (length <= 0):
print("Error: end < start.")
exit(1)
print(chr)
print(resolution)
samples = []
for dir in dirs:
observed = dir + "/Matrix/intrachromosomal/" + str(
resolution) + "/observed." + type + "." + chr + ".matrix.gz"
eigen = dir + "/Eigen/" + str(
resolution) + "/gd_eigen." + type + "." + chr + ".txt"
samples.append(
JuicerMatrix("RPM", observed, resolution, eigenfile=eigen))
nrow_heatmap = 3
nrow_eigen = 1
nrow_now = 0
### Plot
plt.figure(figsize=(args.xsize, 10))
nrow_feature = int(len(samples) / 3)
nrow = nrow_heatmap + nrow_eigen + nrow_feature + 6
# Hi-C Map
plt.subplot2grid((nrow, 5), (nrow_now, 0), rowspan=nrow_heatmap, colspan=5)
tadfile = dirs[0] + "/contact_domain/" + str(resolution) + "_blocks.bedpe"
print(tadfile)
tads = loadTADs(tadfile, chr[3:], start=figstart, end=figend)
loopfile = dirs[0] + "/loops/merged_loops.bedpe"
print(loopfile)
loops = loadloops(loopfile, chr[3:], start=figstart, end=figend)
drawHeatmapTriangle(plt,
samples[0].getmatrix(),
resolution,
figstart=figstart,
figend=figend,
tads=tads,
loops=loops,
vmax=vmax,
vmin=vmin,
distancemax=args.vizdistancemax,
label=labels[0],
xticks=False)
nrow_now += nrow_heatmap
# Compartment
plt.subplot2grid((nrow, 5), (nrow_now, 0), rowspan=nrow_eigen, colspan=4)
plt.plot(samples[0].getEigen())
plt.xlim([s, e])
xtickoff(plt)
nrow_now += nrow_eigen
plotDirectionalFreqRatio(plt, samples, resolution, figstart, figend,
labels, nrow, nrow_now, nrow_feature, args)
plt.savefig(args.output + ".pdf")
def main():
parser = argparse.ArgumentParser()
tp = lambda x: list(map(str, x.split(':')))
parser.add_argument("input",
help="<Input direcoty>:<label>",
type=tp,
nargs='*')
parser.add_argument("output", help="Output prefix", type=str)
parser.add_argument("chr", help="chromosome", type=str)
parser.add_argument("--type",
help="normalize type",
type=str,
default="KR")
parser.add_argument("--distance",
help="distance for DI",
type=int,
default=500000)
parser.add_argument("-r",
"--resolution",
help="resolution",
type=int,
default=25000)
parser.add_argument("-s", "--start", help="start bp", type=int, default=0)
parser.add_argument("-e",
"--end",
help="end bp",
type=int,
default=1000000)
parser.add_argument("--multi",
help="plot MultiInsulation Score",
action='store_true')
parser.add_argument("--multidiff",
help="plot differential MultiInsulation Score",
action='store_true')
parser.add_argument("--compartment",
help="plot Compartment (eigen)",
action='store_true')
parser.add_argument("--di",
help="plot Directionaly Index",
action='store_true')
parser.add_argument("--dfr",
help="plot DirectionalFreqRatio",
action='store_true')
parser.add_argument("--dfr_right",
help="(with --dfr) plot DirectionalFreqRatio (Right)",
action='store_true')
parser.add_argument("--dfr_left",
help="(with --dfr) plot DirectionalFreqRatio (Left)",
action='store_true')
parser.add_argument("--v4c",
help="plot virtual 4C from Hi-C data",
action='store_true')
parser.add_argument("--vmax",
help="max value of color bar",
type=int,
default=50)
parser.add_argument("--vmin",
help="min value of color bar",
type=int,
default=0)
parser.add_argument("--anchor",
help="(for --v4c) anchor point",
type=int,
default=500000)
parser.add_argument("-d",
"--vizdistancemax",
help="max distance in heatmap",
type=int,
default=0)
parser.add_argument("--xsize",
help="xsize for figure",
type=int,
default=10)
# parser.add_argument("--ysize", help="ysize (* times of samples)", type=int, default=3)
args = parser.parse_args()
# print(args)
dirs = []
labels = []
for input in args.input:
dirs.append(input[0])
if (len(input) > 1):
labels.append(input[1])
else:
labels.append("")
chr = args.chr
resolution = args.resolution
type = args.type
figstart = args.start
figend = args.end
s = int(figstart / resolution)
e = int(figend / resolution)
length = figend - figstart
binnum = e - s
vmax = args.vmax
vmin = args.vmin
print("width: " + str(length) + ", " + str(binnum) + " bins.")
if (length <= 0):
print("Error: end < start.")
exit(1)
print(chr)
print(resolution)
samples = []
for dir in dirs:
observed = dir + "/Matrix/intrachromosomal/" + str(
resolution) + "/observed." + type + "." + chr + ".matrix.gz"
eigen = dir + "/Eigen/" + str(
resolution) + "/gd_eigen." + type + "." + chr + ".txt"
samples.append(
JuicerMatrix("RPM", observed, resolution, eigenfile=eigen))
nrow_heatmap = 3
nrow_eigen = 1
nrow_now = 0
### Plot
if (args.multi or args.multidiff or args.v4c):
plt.figure(figsize=(args.xsize, 6 + len(samples)))
nrow = nrow_heatmap + nrow_eigen + len(samples)
else:
plt.figure(figsize=(args.xsize, 6))
nrow_feature = int(len(samples) / 3)
nrow = nrow_heatmap + nrow_eigen + nrow_feature + 2
# Hi-C Map
plt.subplot2grid((nrow, 5), (nrow_now, 0), rowspan=nrow_heatmap, colspan=5)
tadfile = dirs[0] + "/TAD/" + type + str(
resolution
) + "_blocks.bedpe" # tadfile = dirs[0] + "/contact_domain/" + str(resolution) + "_blocks.bedpe"
print(tadfile)
tads = loadTADs(tadfile, chr[3:], start=figstart, end=figend)
loopfile = dirs[
0] + "/loops/" + type + "merged_loops.bedpe" # loopfile = dirs[0] + "/loops/merged_loops.bedpe"
print(loopfile)
loops = loadloops(loopfile, chr[3:], start=figstart, end=figend)
drawHeatmapTriangle(plt,
samples[0].getmatrix(),
resolution,
figstart=figstart,
figend=figend,
tads=tads,
loops=loops,
vmax=vmax,
vmin=vmin,
distancemax=args.vizdistancemax,
label=labels[0],
xticks=False)
nrow_now += nrow_heatmap
# Compartment
# plt.subplot2grid((nrow, 5), (nrow_now, 0), rowspan=nrow_eigen, colspan=4)
# plt.plot(samples[0].getEigen())
# plt.xlim([s,e])
# xtickoff(plt)
# nrow_now += nrow_eigen
if (args.dfr): # Directional Frequency Ratio
plotDirectionalFreqRatio(plt, samples, resolution, figstart, figend,
labels, nrow, nrow_now, nrow_feature, args)
elif (args.di): # Directionality Index
plt.subplot2grid((nrow, 5), (nrow_now, 0),
rowspan=nrow_feature,
colspan=5)
vDI = getDirectionalityIndexOfMultiSample(samples,
labels,
distance=args.distance)
plt.imshow(vDI.iloc[:, s:e],
clim=(-1000, 1000),
cmap=generate_cmap(['#1310cc', '#FFFFFF', '#d10a3f']),
aspect="auto")
plt.colorbar()
pltxticks(0, e - s, figstart, figend, 10)
plt.yticks(np.arange(len(labels)), labels)
elif (args.compartment): # Compartment
for i, sample in enumerate(samples):
if i == 0: Matrix = sample.getEigen()
else: Matrix = np.vstack((Matrix, sample.getEigen()))
plt.subplot2grid((nrow, 5), (nrow_now, 0),
rowspan=nrow_feature,
colspan=5)
plt.imshow(Matrix[:, s:e],
clim=(-0.05, 0.05),
cmap=generate_cmap(['#1310cc', '#FFFFFF', '#d10a3f']),
aspect="auto")
plt.colorbar()
plt.yticks(np.arange(len(labels)), labels)
xtickoff(plt)
nrow_now += nrow_feature
plt.subplot2grid((nrow, 5), (nrow_now, 0), rowspan=2, colspan=4)
for i, sample in enumerate(samples):
plt.plot(sample.getEigen(), label=labels[i])
plt.xlim([s, e])
pltxticks(s, e, figstart, figend, 10)
elif (args.v4c): # virtual 4c
a = int(args.anchor / resolution)
for i, sample in enumerate(samples):
plt.subplot2grid((nrow, 5), (i + nrow_now, 0),
rowspan=1,
colspan=4)
array = sample.getmatrix().iloc[a, s:e]
plt.plot(array, color="k")
plt.title(labels[i])
pltxticks(0, e - s, figstart, figend, 10)
plt.ylim(vmin, vmax)
# plt.yscale('log')
if s < a and a < e:
plt.axvline(x=a - s)
plt.tight_layout()
elif (args.multi): # Multi Insulation score
for i, sample in enumerate(samples):
plt.subplot2grid((nrow, 5), (i + nrow_now, 0),
rowspan=1,
colspan=5)
MI = sample.getMultiInsulationScore()
plt.imshow(MI.T.iloc[:, s:e],
clim=(0.4, 1.0),
cmap=generate_cmap(['#d10a3f', '#FFFFFF', '#1310cc']),
aspect="auto")
plt.title(labels[i])
pltxticks(0, e - s, figstart, figend, 10)
# plt.yticks([2], (labels[i]))
# plt.xlim([s,e])
# pltxticks(s, e, figstart, figend, 10)
plt.colorbar()
plt.tight_layout()
elif (args.multidiff): # differential Multi Insulation score
for i, sample in enumerate(samples):
if i == 0:
MIref = sample.getMultiInsulationScore()
continue
plt.subplot2grid((nrow, 5), (i - 1 + nrow_now, 0),
rowspan=1,
colspan=5)
MI = sample.getMultiInsulationScore()
plt.imshow(MI.T.iloc[:, s:e] - MIref.T.iloc[:, s:e],
clim=(-0.4, 0.4),
cmap=generate_cmap(['#d10a3f', '#FFFFFF', '#1310cc']),
aspect="auto")
plt.title(labels[i])
pltxticks(0, e - s, figstart, figend, 10)
plt.colorbar()
plt.tight_layout()
else: # Single Insulation score
Matrix = getInsulationScoreOfMultiSample(samples, labels)
plt.subplot2grid((nrow, 5), (nrow_now, 0),
rowspan=nrow_feature,
colspan=5)
plt.imshow(Matrix.T.iloc[:, s:e],
clim=(0.4, 1.0),
cmap=generate_cmap(['#d10a3f', '#FFFFFF', '#1310cc']),
aspect="auto")
plt.colorbar()
pltxticks(0, e - s, figstart, figend, 10)
plt.yticks(np.arange(len(labels)), labels)
nrow_now += nrow_feature
plt.subplot2grid((nrow, 5), (nrow_now, 0), rowspan=2, colspan=4)
for i in range(len(samples)):
plt.plot(Matrix.iloc[s:e, i], label=labels[i])
plt.xlim([figstart, figend])
# plt.legend()
plt.savefig(args.output + ".pdf")
def main():
parser = argparse.ArgumentParser()
tp = lambda x: list(map(str, x.split(':')))
parser.add_argument("input",
help="<Input direcoty>:<label>",
type=tp,
nargs='*')
parser.add_argument("output", help="Output prefix", type=str)
parser.add_argument("chr", help="chromosome", type=str)
parser.add_argument("--type",
help="normalize type",
type=str,
default="KR")
parser.add_argument("-r",
"--resolution",
help="resolution",
type=int,
default=25000)
parser.add_argument("-s", "--start", help="start bp", type=int, default=0)
parser.add_argument("-e",
"--end",
help="end bp",
type=int,
default=1000000)
parser.add_argument("--vmax",
help="max value of color bar",
type=int,
default=1)
parser.add_argument("--vmin",
help="min value of color bar",
type=int,
default=-1)
parser.add_argument("--xsize",
help="xsize for figure",
type=int,
default=3)
parser.add_argument("--ysize",
help="ysize (* times of samples)",
type=int,
default=3)
args = parser.parse_args()
# print(args)
dirs = []
labels = []
for input in args.input:
dirs.append(input[0])
if (len(input) > 1):
labels.append(input[1])
else:
labels.append("")
chr = args.chr
resolution = args.resolution
type = args.type
figstart = args.start
figend = args.end
s = int(figstart / resolution)
e = int(figend / resolution)
vmax = args.vmax
vmin = args.vmin
print(chr)
print(resolution)
samples = []
for dir in dirs:
observed = dir + "/Matrix/intrachromosomal/" + str(
resolution) + "/observed." + type + "." + chr + ".matrix.gz"
samples.append(JuicerMatrix("RPM", observed, resolution))
### Plot
# smooth_median_filter = 3
# EnrichMatrices = make3dmatrixRatio(samples, smooth_median_filter)
EnrichMatrices = make3dmatrixRatio(samples, 3)
nsample = len(samples)
plt.figure(figsize=(nsample * args.xsize / 2, args.ysize * 2))
for i, sample in enumerate(EnrichMatrices):
# Hi-C Map
plt.subplot(2, len(samples) / 2, i + 2)
drawHeatmapSquare(plt,
sample,
resolution,
figstart=figstart,
figend=figend,
vmax=vmax,
vmin=vmin,
cmap=generate_cmap(['#1310cc', '#FFFFFF',
'#d10a3f']),
label=labels[i + 1],
xticks=False)
plt.tight_layout()
plt.savefig(args.output + ".pdf")
def main():
parser = argparse.ArgumentParser()
tp = lambda x: list(map(str, x.split(':')))
parser.add_argument("input",
help="<Input direcoty>:<label>",
type=tp,
nargs='*')
parser.add_argument("output", help="Output prefix", type=str)
parser.add_argument("chr", help="chromosome", type=str)
parser.add_argument("--type",
help="normalize type",
type=str,
default="KR")
parser.add_argument("-r",
"--resolution",
help="resolution",
type=int,
default=25000)
parser.add_argument("-s", "--start", help="start bp", type=int, default=0)
parser.add_argument("-e",
"--end",
help="end bp",
type=int,
default=1000000)
parser.add_argument("--vmax",
help="max value of color bar",
type=int,
default=1)
parser.add_argument("--vmin",
help="min value of color bar",
type=int,
default=-1)
parser.add_argument("--xsize",
help="xsize for figure",
type=int,
default=3)
parser.add_argument("--ysize",
help="ysize (* times of samples)",
type=int,
default=3)
args = parser.parse_args()
# print(args)
dirs = []
labels = []
for input in args.input:
dirs.append(input[0])
if (len(input) > 1):
labels.append(input[1])
else:
labels.append("")
chr = args.chr
resolution = args.resolution
type = args.type
figstart = args.start
figend = args.end
s = int(figstart / resolution)
e = int(figend / resolution)
vmax = args.vmax
vmin = args.vmin
print(chr)
print(resolution)
samples = []
for dir in dirs:
# observed = dir + "/Matrix/intrachromosomal/" + str(resolution) + "/observed." + type + "." + chr + ".matrix.gz"
samples.append(JuicerMatrix("RPM", dir, resolution))
smooth_median_filter = 3
mt1 = make3dmatrixRatio([samples[0], samples[1]], smooth_median_filter)
mt2 = make3dmatrixRatio([samples[2], samples[3]], smooth_median_filter)
# Combined = np.concatenate((mt1), axis=0)
matrix = np.triu(mt1[0], k=1) + np.tril(mt2[0], k=-1)
if (labels[1] != "" and labels[3] != ""):
label = labels[1] + "-" + labels[3]
else:
label = ""
plt.subplot(1, 1, 1)
drawHeatmapSquare(plt,
matrix,
resolution,
figstart=figstart,
figend=figend,
vmax=vmax,
vmin=vmin,
cmap=generate_cmap(['#1310cc', '#FFFFFF', '#d10a3f']),
label=label,
xticks=False)
plt.savefig(args.output + ".pdf")