def test_highlight_plot(self, crange):
bplot = kplot.BigWigPlot(self.bigwig_path)
gplot = kplot.GenePlot(self.gtf_path)
high = kplot.HighlightAnnotation(self.peak_path)
gfig = kplot.GenomicFigure([bplot, gplot, high])
fig, axes = gfig.plot("chr11:{}-{}".format(*crange))
p1 = high.patches[0]
assert gplot.ax.transAxes.transform(
(0,
0))[1] == pytest.approx(p1._transform.transform(p1.get_xy())[1])
def test_geneplot(self, collapse, squash_group):
squash, group_by = squash_group
gplot = kplot.GenePlot(self.gtf_path,
collapse=collapse,
squash=squash,
group_by=group_by)
gfig = kplot.GenomicFigure([gplot])
selector = "chr11:77490000-77500000"
fig, axes = gfig.plot(selector)
assert len(axes[0].patches) == (19 if squash else 49)
plt.close(fig)
def test_invert_x_independent_x(self, crange):
offset = 150000
bplot = kplot.BigWigPlot(self.bigwig_path)
gplot = kplot.GenePlot(self.gtf_path)
gfig = kplot.GenomicFigure([bplot, gplot], invert_x=True)
fig, axes = gfig.plot("chr11:{}-{}".format(*crange))
ax_lim = axes[0].get_xlim()
assert (ax_lim[0] > ax_lim[1]
for ax_lim in (a.get_xlim() for a in axes))
bplot = kplot.BigWigPlot(self.bigwig_path, invert_x=True)
gplot = kplot.GenePlot(self.gtf_path)
gfig = kplot.GenomicFigure([bplot, gplot], independent_x=True)
fig, axes = gfig.plot([
"chr11:{}-{}".format(*crange),
"chr11:{}-{}".format(crange[0] + offset, crange[1] + offset)
])
ax_lim = [ax.get_xlim() for ax in axes]
abs_tol = 10000
assert ax_lim[0][0] == pytest.approx(crange[1], abs=abs_tol)
assert ax_lim[0][1] == pytest.approx(crange[0], abs=abs_tol)
assert ax_lim[1][0] == pytest.approx(crange[1] + offset, abs=abs_tol)
assert ax_lim[1][1] == pytest.approx(crange[0] + offset, abs=abs_tol)
def gene(parameters):
parser = parsers.gene_parser()
args = parser.parse_args(parameters)
genes_file = os.path.expanduser(args.genes)
p = kplt.GenePlot(genes_file,
feature_types=args.feature_types,
color_neutral=args.color_neutral,
color_forward=args.color_forward,
color_reverse=args.color_reverse,
color_score=args.color_score,
box_height=args.box_height,
font_size=args.font_size,
arrow_size=args.arrow_size,
line_width=args.line_width,
group_by=args.group_by,
show_labels=args.show_labels,
collapse=args.collapse,
squash=args.squash,
label_field=args.label_field)
return p, args
gd7_microc_plot = fancplot.HicPlot(gd7_microc, vmin=1e-03,
vmax=1e-01, norm="log",
draw_minor_ticks=False, title="gd7")
control_microc = fanc.load(os.path.join("data", "micro-c", "merged",
"control", "hic",
"control_" + res + ".hic"),
mode="r")
control_microc_plot = fancplot.HicPlot(control_microc, vmin=1e-03,
vmax=1e-01, norm="log",
draw_minor_ticks=False, title="control")
genes = "external_data/flybase/dmel-all-r6.30.gtf.gz"
genes_plot = fancplot.GenePlot(genes, squash=True, group_by="gene_symbol",
aspect=0.15, label_field="gene_symbol",
show_labels=False, draw_minor_ticks=False)
rnaseq_dict = {name: os.path.join("external_data", "koenecke_2016_2017", "rnaseq_aligned",
name + "_sorted_filtered_merged_canonical_chrs_rnaseq.bw")
for name in ["gd7", "tlrm910", "tl10b"]}
h3k27ac_dict = {name: os.path.join("external_data", "koenecke_2016_2017", "chipseq_aligned",
"H3K27ac_" + name + "_sorted_filtered_merged_canonical_chrs.bw")
for name in ["gd7", "tl10b"]}
h3k27ac_dict["Tollrm910"] = os.path.join("external_data", "extra_chip-seq", "chipseq_aligned",
"H3K27ac_Tollrm910_sorted_filtered_merged_canonical_chrs.bw")
h3k27me3_dict = {name: os.path.join("external_data", "koenecke_2016_2017", "chipseq_aligned",
"H3K27me3_" + name + "_sorted_filtered_merged_canonical_chrs.bw")
for name in ["gd7", "tl10b"]}
def plot_regions(regions):
h = fanc.load(os.path.join("data", "hic", "merged", "3-4h", "hic",
"3-4h_2kb.hic"),
mode="r")
h_plot = fancplot.HicPlot(h,
vmin=1e-03,
vmax=1e-01,
norm="log",
draw_minor_ticks=False)
genes = "external_data/flybase/dmel-all-r6.30.gtf.gz"
genes_plot = fancplot.GenePlot(genes,
squash=True,
group_by="gene_symbol",
aspect=0.15,
label_field="gene_symbol",
show_labels=False,
draw_minor_ticks=False)
rnaseq_dict = {
name:
os.path.join("external_data", "koenecke_2016_2017", "rnaseq_aligned",
name + "_sorted_filtered_merged_canonical_chrs_rnaseq.bw")
for name in ["gd7", "tlrm910", "tl10b"]
}
h3k27ac_dict = {
name: os.path.join(
"external_data", "koenecke_2016_2017", "chipseq_aligned",
"H3K27ac_" + name + "_sorted_filtered_merged_canonical_chrs.bw")
for name in ["gd7", "tl10b"]
}
h3k27ac_dict["Tollrm910"] = os.path.join(
"external_data", "extra_chip-seq", "chipseq_aligned",
"H3K27ac_Tollrm910_sorted_filtered_merged_canonical_chrs.bw")
rnaseq_ylim = fancplot.helpers.LimitGroup()
h3k27ac_ylim = fancplot.helpers.LimitGroup()
polii_ylim = fancplot.helpers.LimitGroup()
# polii_chip_early = os.path.join("external_data", "blythe_2015", "aligned",
# "PolII-pSer5_NC14-early_sorted_filtered_merged_canonical_chrs.bw")
# polii_chip_mid = os.path.join("external_data", "blythe_2015", "aligned",
# "PolII-pSer5_NC14-middle_sorted_filtered_merged_canonical_chrs.bw")
polii_chip_late = os.path.join(
"external_data", "blythe_2015", "aligned",
"PolII-pSer5_NC14-late_sorted_filtered_merged_canonical_chrs.bw")
# polii_early_plot = fancplot.LinePlot(polii_chip_early, fill=True, plot_kwargs={'color': "black"},
# draw_minor_ticks=False, aspect=0.05,
# ylim=polii_ylim, n_yticks=2)
# polii_mid_plot = fancplot.LinePlot(polii_chip_mid, fill=True, plot_kwargs={'color': "black"},
# draw_minor_ticks=False, aspect=0.05,
# ylim=polii_ylim, n_yticks=2)
polii_late_plot = fancplot.LinePlot(polii_chip_late,
fill=True,
plot_kwargs={'color': "black"},
draw_minor_ticks=False,
aspect=0.05,
ylim=polii_ylim,
n_yticks=2)
rnaseq_plot_gd7 = fancplot.LinePlot(rnaseq_dict['gd7'],
fill=True,
plot_kwargs={'color': "#648fff"},
draw_minor_ticks=False,
aspect=0.05,
n_yticks=2)
h3k27ac_plot_gd7 = fancplot.LinePlot(h3k27ac_dict['gd7'],
fill=True,
plot_kwargs={'color': "#648fff"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27ac_ylim,
n_yticks=2)
rnaseq_plot_Tollrm910 = fancplot.LinePlot(rnaseq_dict['tlrm910'],
fill=True,
plot_kwargs={'color': "#dc267f"},
draw_minor_ticks=False,
aspect=0.05,
n_yticks=2)
h3k27ac_plot_Tollrm910 = fancplot.LinePlot(
h3k27ac_dict['Tollrm910'],
fill=True,
plot_kwargs={'color': "#dc267f"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27ac_ylim,
n_yticks=2)
rnaseq_plot_toll10b = fancplot.LinePlot(rnaseq_dict['tl10b'],
fill=True,
plot_kwargs={'color': "#ffb000"},
draw_minor_ticks=False,
aspect=0.05,
n_yticks=2)
h3k27ac_plot_toll10b = fancplot.LinePlot(h3k27ac_dict['tl10b'],
fill=True,
plot_kwargs={'color': "#ffb000"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27ac_ylim,
n_yticks=2)
gd7_enh = "data/supplementary_tables/gd7_candidate_enhancers.bed"
gd7_enh_plot = fancplot.GenomicFeaturePlot(gd7_enh,
aspect=0.02,
color="#648fff",
draw_minor_ticks=False)
Tollrm910_enh = "data/supplementary_tables/Tollrm910_candidate_enhancers.bed"
Tollrm910_enh_plot = fancplot.GenomicFeaturePlot(Tollrm910_enh,
aspect=0.02,
color="#dc267f",
draw_minor_ticks=False)
toll10b_enh = "data/supplementary_tables/Toll10B_candidate_enhancers.bed"
toll10b_enh_plot = fancplot.GenomicFeaturePlot(toll10b_enh,
aspect=0.02,
color="#ffb000",
draw_minor_ticks=False)
plots = [
h_plot,
# ins_plot,
# boundaries_plot,
genes_plot,
# hk_plot,
# polii_early_plot, polii_mid_plot,
polii_late_plot,
rnaseq_plot_gd7,
rnaseq_plot_Tollrm910,
rnaseq_plot_toll10b,
h3k27ac_plot_gd7,
h3k27ac_plot_Tollrm910,
h3k27ac_plot_toll10b,
gd7_enh_plot,
Tollrm910_enh_plot,
toll10b_enh_plot
]
with PdfPages(output_file) as pdf:
with fancplot.GenomicFigure(plots, ticks_last=True) as gfig:
for name, region, rnaseq_ylim in regions:
logging.info(region)
fig, axes = gfig.plot(region)
axes[3].set_ylim([0, rnaseq_ylim])
axes[4].set_ylim([0, rnaseq_ylim])
axes[5].set_ylim([0, rnaseq_ylim])
pdf.savefig()
def plot_region(name, region):
output_file = os.path.join("figures", "figure_4_panels", name + ".pdf")
logging.info("Working on %s", name)
logging.info("Will write output to %s", output_file)
gd7_nc14_hic = fanc.load(os.path.join("data", "hic", "merged", "gd7-nc14",
"hic", "gd7-nc14_5kb.hic"),
mode="r")
gd7_nc14_hic_plot = fancplot.HicPlot(gd7_nc14_hic,
norm="log",
vmin=1e-03,
vmax=1e-01,
draw_minor_ticks=False,
title="gd7",
max_dist='250kb')
gd7_nc14_diff = fanc.load(os.path.join(
"data", "hic", "merged", "gd7-nc14", "hic",
"diff_control-nc14_gd7-nc14_5kb.hic"),
mode="r")
gd7_nc14_diff_plot = fancplot.HicPlot(gd7_nc14_diff,
norm="lin",
colormap='bwr_r',
vmin=-0.01,
vmax=0.01,
draw_minor_ticks=False,
max_dist='250kb')
Tollrm910_nc14_hic = fanc.load(os.path.join("data", "hic", "merged",
"Tollrm910-nc14", "hic",
"Tollrm910-nc14_5kb.hic"),
mode="r")
Tollrm910_nc14_hic_plot = fancplot.HicPlot(Tollrm910_nc14_hic,
norm="log",
vmin=1e-03,
vmax=1e-01,
draw_minor_ticks=False,
title="Tollrm910",
max_dist='250kb')
Tollrm910_nc14_diff = fanc.load(os.path.join(
"data", "hic", "merged", "Tollrm910-nc14", "hic",
"diff_control-nc14_Tollrm910-nc14_5kb.hic"),
mode="r")
Tollrm910_nc14_diff_plot = fancplot.HicPlot(Tollrm910_nc14_diff,
norm="lin",
colormap='bwr_r',
vmin=-0.01,
vmax=0.01,
draw_minor_ticks=False,
max_dist='250kb')
Toll10B_nc14_hic = fanc.load(os.path.join("data", "hic", "merged",
"Toll10B-nc14", "hic",
"Toll10B-nc14_5kb.hic"),
mode="r")
Toll10B_nc14_hic_plot = fancplot.HicPlot(Toll10B_nc14_hic,
norm="log",
vmin=1e-03,
vmax=1e-01,
draw_minor_ticks=False,
title="Toll10B",
max_dist='250kb')
Toll10B_nc14_diff = fanc.load(os.path.join(
"data", "hic", "merged", "Toll10B-nc14", "hic",
"diff_control-nc14_Toll10B-nc14_5kb.hic"),
mode="r")
Toll10B_nc14_diff_plot = fancplot.HicPlot(Toll10B_nc14_diff,
norm="lin",
colormap='bwr_r',
vmin=-0.01,
vmax=0.01,
draw_minor_ticks=False,
max_dist='250kb')
genes = "external_data/flybase/dmel-all-r6.30.gtf.gz"
genes_plot = fancplot.GenePlot(genes,
squash=True,
group_by="gene_symbol",
aspect=0.15,
label_field="gene_symbol",
show_labels=False,
draw_minor_ticks=False)
rnaseq_dict = {
name:
os.path.join("external_data", "koenecke_2016_2017", "rnaseq_aligned",
name + "_sorted_filtered_merged_canonical_chrs_rnaseq.bw")
for name in ["gd7", "tlrm910", "tl10b"]
}
h3k27ac_dict = {
name: os.path.join(
"external_data", "koenecke_2016_2017", "chipseq_aligned",
"H3K27ac_" + name + "_sorted_filtered_merged_canonical_chrs.bw")
for name in ["gd7", "tl10b"]
}
h3k27ac_dict["Tollrm910"] = os.path.join(
"external_data", "extra_chip-seq", "chipseq_aligned",
"H3K27ac_Tollrm910_sorted_filtered_merged_canonical_chrs.bw")
h3k27me3_dict = {
name: os.path.join(
"external_data", "koenecke_2016_2017", "chipseq_aligned",
"H3K27me3_" + name + "_sorted_filtered_merged_canonical_chrs.bw")
for name in ["gd7", "tl10b"]
}
h3k27me3_dict["Tollrm910"] = os.path.join(
"external_data", "extra_chip-seq", "chipseq_aligned",
"H3K27me3_Tollrm910_sorted_filtered_merged_canonical_chrs.bw")
# ins_dict = {name: os.path.join("data", "boundaries", name + "_2kb_8.bw")
# for name in ["gd7-nc14", "Tollrm910-nc14", "Toll10B-nc14", "3-4h"]}
rnaseq_ylim = fancplot.helpers.LimitGroup()
rnaseq_ylim = [0, 10]
h3k27ac_ylim = fancplot.helpers.LimitGroup()
h3k27me3_ylim = fancplot.helpers.LimitGroup()
rnaseq_plot_gd7 = fancplot.LinePlot(rnaseq_dict['gd7'],
fill=False,
plot_kwargs={'color': "#648fff"},
draw_minor_ticks=False,
aspect=0.05,
ylim=rnaseq_ylim,
n_yticks=2)
h3k27ac_plot_gd7 = fancplot.LinePlot(h3k27ac_dict['gd7'],
fill=False,
plot_kwargs={'color': "#648fff"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27ac_ylim,
n_yticks=2)
h3k27me3_plot_gd7 = fancplot.LinePlot(h3k27me3_dict['gd7'],
fill=False,
plot_kwargs={'color': "#648fff"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27me3_ylim,
n_yticks=2)
rnaseq_plot_Tollrm910 = fancplot.LinePlot(rnaseq_dict['tlrm910'],
fill=False,
plot_kwargs={'color': "#dc267f"},
draw_minor_ticks=False,
aspect=0.05,
ylim=rnaseq_ylim,
n_yticks=2)
h3k27ac_plot_Tollrm910 = fancplot.LinePlot(
h3k27ac_dict['Tollrm910'],
fill=False,
plot_kwargs={'color': "#dc267f"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27ac_ylim,
n_yticks=2)
h3k27me3_plot_Tollrm910 = fancplot.LinePlot(
h3k27me3_dict['Tollrm910'],
fill=False,
plot_kwargs={'color': "#dc267f"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27me3_ylim,
n_yticks=2)
rnaseq_plot_toll10b = fancplot.LinePlot(rnaseq_dict['tl10b'],
fill=False,
plot_kwargs={'color': "#ffb000"},
draw_minor_ticks=False,
aspect=0.05,
ylim=rnaseq_ylim,
n_yticks=2)
h3k27ac_plot_toll10b = fancplot.LinePlot(h3k27ac_dict['tl10b'],
fill=False,
plot_kwargs={'color': "#ffb000"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27ac_ylim,
n_yticks=2)
h3k27me3_plot_toll10b = fancplot.LinePlot(h3k27me3_dict['tl10b'],
fill=False,
plot_kwargs={'color': "#ffb000"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27me3_ylim,
n_yticks=2)
gd7_enh = "data/supplementary_tables/gd7_candidate_enhancers.bed"
gd7_enh_plot = fancplot.GenomicFeaturePlot(gd7_enh,
aspect=0.02,
color="#648fff",
draw_minor_ticks=False)
Tollrm910_enh = "data/supplementary_tables/Tollrm910_candidate_enhancers.bed"
Tollrm910_enh_plot = fancplot.GenomicFeaturePlot(Tollrm910_enh,
aspect=0.02,
color="#dc267f",
draw_minor_ticks=False)
toll10b_enh = "data/supplementary_tables/Toll10B_candidate_enhancers.bed"
toll10b_enh_plot = fancplot.GenomicFeaturePlot(toll10b_enh,
aspect=0.02,
color="#ffb000",
draw_minor_ticks=False)
plots = [
gd7_nc14_hic_plot, gd7_nc14_diff_plot, rnaseq_plot_gd7,
h3k27ac_plot_gd7, gd7_enh_plot, h3k27me3_plot_gd7,
Tollrm910_nc14_hic_plot, Tollrm910_nc14_diff_plot,
rnaseq_plot_Tollrm910, h3k27ac_plot_Tollrm910, Tollrm910_enh_plot,
h3k27me3_plot_Tollrm910, Toll10B_nc14_hic_plot, Toll10B_nc14_diff_plot,
rnaseq_plot_toll10b, h3k27ac_plot_toll10b, toll10b_enh_plot,
h3k27me3_plot_toll10b, genes_plot
]
with fancplot.GenomicFigure(plots, ticks_last=True) as gfig:
fig, axes = gfig.plot(region)
fig.savefig(output_file)
p_dir = fancplot.LinePlot(directionality_single, ax=ax_dir, style='mid', plot_kwargs={'color': '#79C7C5'},
draw_tick_legend=False, draw_minor_ticks=False)
p_dir.plot(triangular_plotting_region)
ax_dir.set_xticks([triangular_plotting_region.start,
triangular_plotting_region.center,
triangular_plotting_region.end])
ax_dir.set_ylabel('Directionality\nindex 1Mb')
# 13. Genes
genes = fanc.load(genes_file)
p_genes = fancplot.GenePlot(genes, feature_types=('exon',),
color_score=False, box_height=0.9, show_labels=True,
label_field='gene_name', font_size=7, arrow_size=0, show_arrows=False,
line_width=1, group_by='gene_id', draw_tick_legend=False,
draw_tick_labels=True, draw_minor_ticks=False,
ax=ax_genes, squash=True, min_gene_size=3000,
collapse=False,
include={
'gene_type': {'processed_transcript', 'rRNA',
'protein_coding', 'IG_V_gene'}
})
p_genes.plot(triangular_plotting_region)
ax_genes.set_xticks([triangular_plotting_region.start,
triangular_plotting_region.center,
triangular_plotting_region.end])
# 14. CTCF enrichment
p_ctcf = fancplot.LinePlot(ctcf, ax=ax_ctcf, style='mid', plot_kwargs={'color': 'black'}, fill=False,
draw_tick_labels=False)
p_ctcf.plot(triangular_plotting_region)
ax_ctcf.set_xticks([triangular_plotting_region.start,