DNA Methylation vs Gene Expression

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(654)

# Methylation sites on chromosome
n_sites = 200

# Position along chromosome
position = np.sort(np.random.uniform(0, 100, n_sites))  # Mbp

# Methylation level (beta value 0-1)
methylation = np.random.beta(2, 5, n_sites)

# Expression correlation
expression = -0.5 * methylation + np.random.normal(0, 0.2, n_sites) + 0.5

fig = plt.figure(figsize=(10, 8), facecolor='#0a0a0f')
ax = fig.add_subplot(111, projection='3d', facecolor='#0a0a0f')

scatter = ax.scatter(position, methylation, expression, c=methylation, 
                     cmap='RdYlGn_r', s=40, alpha=0.7, edgecolors='none')

ax.set_xlabel('Position (Mbp)', color='white', fontsize=10)
ax.set_ylabel('Methylation (β)', color='white', fontsize=10)
ax.set_zlabel('Expression', color='white', fontsize=10)
ax.set_title('DNA Methylation vs Gene Expression', color='white', fontsize=14, fontweight='bold', pad=20)

ax.tick_params(colors='#64748b', labelsize=8)
ax.xaxis.pane.fill = False
ax.yaxis.pane.fill = False
ax.zaxis.pane.fill = False
ax.xaxis.pane.set_edgecolor('#1e293b')
ax.yaxis.pane.set_edgecolor('#1e293b')
ax.zaxis.pane.set_edgecolor('#1e293b')

ax.view_init(elev=20, azim=35)
plt.tight_layout()
plt.show()