Gene Expression by Tissue

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np

np.random.seed(123)

tissues = ['Brain', 'Liver', 'Heart', 'Kidney']
data = []
for tissue in tissues:
    n = 35
    age = np.random.uniform(20, 80, n)
    slopes = {'Brain': -0.015, 'Liver': -0.02, 'Heart': -0.012, 'Kidney': -0.018}
    expression = 100 + slopes[tissue] * age * 10 + np.random.normal(0, 8, n)
    for a, e in zip(age, expression):
        data.append({'Age': a, 'Expression Level': e, 'Tissue': tissue})

df = pd.DataFrame(data)

plt.style.use('dark_background')
sns.set_style("darkgrid", {
    'axes.facecolor': '#0a0a0f',
    'figure.facecolor': '#0a0a0f',
    'grid.color': '#333333'
})

palette = ['#5314E6', '#F5D327', '#27F5B0', '#C82909']

g = sns.lmplot(
    data=df,
    x='Age',
    y='Expression Level',
    hue='Tissue',
    col='Tissue',
    col_wrap=2,
    height=3.5,
    aspect=1.2,
    palette=palette,
    scatter_kws={'alpha': 0.75, 's': 45, 'edgecolor': 'white', 'linewidths': 0.4},
    line_kws={'linewidth': 2.5},
    ci=95
)

g.fig.set_facecolor('#0a0a0f')
for ax in g.axes.flat:
    ax.set_facecolor('#0a0a0f')
    for spine in ax.spines.values():
        spine.set_color('#333333')

g.fig.suptitle('Age-Related Gene Expression Decline', fontsize=14, fontweight='bold', color='white', y=1.02)
plt.tight_layout()
plt.show()