Microbiome Abundance Heatmap

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

np.random.seed(42)

# Simulated microbiome data
species = ['Bacteroides', 'Prevotella', 'Faecalibact.', 'Roseburia', 
           'Bifidobact.', 'Lactobacillus', 'Akkermansia', 'Ruminococcus',
           'Blautia', 'Clostridium', 'Streptococcus', 'Escherichia']
samples = [f'S{i:02d}' for i in range(1, 17)]

# Create abundance data with enterotype-like structure
data = np.random.exponential(1, (len(species), len(samples)))
data[0, :5] *= 3
data[1, 5:10] *= 3
data[4:6, 10:] *= 2

df = pd.DataFrame(np.log10(data + 0.01), index=species, columns=samples)

# NEON colormap
neon_cmap = LinearSegmentedColormap.from_list('neon', ['#0a0a0f', '#4927F5', '#27D3F5', '#6CF527', '#F5B027'])

fig, ax = plt.subplots(figsize=(10, 7), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

# Create heatmap
sns.heatmap(df, cmap=neon_cmap, linewidths=0.5, linecolor='#1a1a2e',
            cbar_kws={'shrink': 0.6, 'label': 'Log₁₀ Abundance'},
            ax=ax)

# Style
ax.set_title('Gut Microbiome Composition', color='white', fontsize=14, fontweight='bold', pad=15)
ax.set_xlabel('Samples', color='white', fontsize=11)
ax.set_ylabel('Bacterial Species', color='white', fontsize=11)

# Tick styling
ax.tick_params(colors='white', labelsize=9)
ax.set_xticklabels(ax.get_xticklabels(), rotation=45, ha='right')
ax.set_yticklabels(ax.get_yticklabels(), rotation=0)

# Colorbar styling
cbar = ax.collections[0].colorbar
cbar.ax.yaxis.set_tick_params(color='white')
cbar.ax.yaxis.label.set_color('white')
plt.setp(cbar.ax.yaxis.get_ticklabels(), color='white', fontsize=9)

plt.tight_layout()
plt.show()