Zooming in chromosomal interaction domains¶

import numpy as np

import matplotlib.pyplot as plt

from circhic import datasets
from circhic import CircHiCFigure

from iced.normalization import ICE_normalization

# Load the data, compute the cumulative raw counts.
data = datasets.load_ccrescentus()
counts_raw = data["counts"]
lengths = data["nbins"]
cumul_raw_counts = counts_raw.sum(axis=0)

# Normalize the data using ICE, and keep the biases
counts, bias = ICE_normalization(counts_raw, output_bias=True)

#compute extreme values
vmax=np.max([counts[i,(i+1)%counts.shape[0]] for i in range(counts.shape[0])])
vmin=np.min(counts[counts>0])

#plotting the data
granularity = 0.5
resolution = 9958

fig = plt.figure(figsize=(6, 6))

inner_radius, outer_radius = 0.4, 0.95
inner_gdis, outer_gdis = 600000, 600000

chrom_lengths = lengths * resolution
circhicfig = CircHiCFigure(chrom_lengths, figure=fig)
m, ax = circhicfig.plot_hic(counts, granularity=granularity, resolution = resolution,
                            outer_radius=outer_radius, inner_radius=inner_radius,
                            inner_gdis=inner_gdis, outer_gdis=outer_gdis,
                            vmin=vmin*100, vmax=vmax, cmap="bone_r",border_thickness=0.005)

rax = circhicfig.plot_raxis()
rax.set_yticklabels(["60", "0", "60"], fontsize="small")
rax.set_ylabel("Genomic distance (kb)", fontsize="small", color="0.3", position=(0,1.03))
rax.tick_params(colors="0.3")

cab = circhicfig.set_colorbar(m, orientation="horizontal")
cab.set_label("Normalized contact counts", fontsize="small")

ticklabels = ["%d kb" % (i * 500) for i in range(7)]
tickpositions= [int(i*500000) for i in range(7)]
ticklabels[0] = "oriC"
ax = circhicfig.set_genomic_ticklabels(
    tickpositions=tickpositions,
    ticklabels=ticklabels,
    outer_radius=0.98,fontdict={'fontsize':"small"})
ax.tick_params(colors="0.3")