Dendrogram

Radial Gene Cluster Dark

Gene expression clustering in true circular dendrogram format

Output
Radial Gene Cluster Dark
Python
import matplotlib.pyplot as plt
import numpy as np
from scipy.cluster.hierarchy import dendrogram, linkage, set_link_color_palette

np.random.seed(456)

genes = ['BRCA1', 'TP53', 'EGFR', 'MYC', 'KRAS', 'PIK3CA', 'PTEN', 'AKT1',
         'BRAF', 'NRAS', 'CDK4', 'MDM2', 'ERBB2', 'ALK', 'ROS1', 'MET']
n = len(genes)
expression = np.random.rand(n, 8) * 100
Z = linkage(expression, method='ward')

fig_temp, ax_temp = plt.subplots()
set_link_color_palette(['#F5276C', '#6CF527', '#27D3F5', '#F5B027', '#5314E6'])
dn = dendrogram(Z, labels=genes, no_plot=False, color_threshold=0.65*max(Z[:,2]),
                above_threshold_color='#444444', ax=ax_temp)
plt.close(fig_temp)

icoord = np.array(dn['icoord'])
dcoord = np.array(dn['dcoord'])
colors = dn['color_list']

x_min, x_max = icoord.min(), icoord.max()
y_max = dcoord.max()

def to_polar(x, y):
    theta = (x - x_min) / (x_max - x_min) * 2 * np.pi * 0.9 + np.pi * 0.05
    r = y / y_max * 0.6 + 0.35
    return theta, r

fig, ax = plt.subplots(figsize=(10, 10), subplot_kw={'projection': 'polar'}, facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

# Draw distance rings
for r in [0.5, 0.7, 0.9]:
    circle_theta = np.linspace(0, 2*np.pi, 100)
    ax.plot(circle_theta, [r]*100, color='#333333', linewidth=0.5, linestyle='--', alpha=0.5)

for ic, dc, color in zip(icoord, dcoord, colors):
    thetas, rs = [], []
    for x, y in zip(ic, dc):
        t, r = to_polar(x, y)
        thetas.append(t)
        rs.append(r)
    
    ax.plot([thetas[0], thetas[1]], [rs[0], rs[1]], color=color, linewidth=2.5, alpha=0.9)
    ax.plot([thetas[2], thetas[3]], [rs[2], rs[3]], color=color, linewidth=2.5, alpha=0.9)
    if thetas[1] != thetas[2]:
        arc_thetas = np.linspace(min(thetas[1], thetas[2]), max(thetas[1], thetas[2]), 40)
        ax.plot(arc_thetas, [rs[1]]*len(arc_thetas), color=color, linewidth=2.5, alpha=0.9)

leaf_positions = np.linspace(x_min, x_max, n)
for i, (pos, label) in enumerate(zip(leaf_positions, dn['ivl'])):
    theta, _ = to_polar(pos, 0)
    rotation = np.degrees(theta) - 90 if np.pi/2 < theta < 3*np.pi/2 else np.degrees(theta) + 90
    ha = 'right' if np.pi/2 < theta < 3*np.pi/2 else 'left'
    ax.text(theta, 0.22, label, ha=ha, va='center', fontsize=8, color='#6CF527',
            rotation=rotation, rotation_mode='anchor')
    
    color = ['#F5276C', '#6CF527', '#27D3F5', '#F5B027', '#5314E6'][i % 5]
    ax.scatter(theta, 0.35, c=color, s=45, zorder=5, edgecolor='white', linewidth=0.5)

ax.set_ylim(0, 1.05)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.spines['polar'].set_visible(False)
ax.grid(False)

ax.set_title('Gene Expression Radial Clustering', fontsize=14, color='white', fontweight='bold', y=1.08)

plt.tight_layout()
plt.show()
Library

Matplotlib

Category

Statistical

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