Genomic Variant Light Theme

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)

variants = ['Missense', 'Nonsense', 'Frameshift', 'Splice', 'Synonymous',
            'UTR_5', 'UTR_3', 'Intronic', 'Promoter', 'Enhancer']
genes = ['TP53', 'BRCA1', 'EGFR', 'KRAS', 'PIK3CA', 'PTEN', 'APC', 'MYC']

data = np.random.rand(10, 8) * 3
data[0, 0] += 4  # TP53 missense
data[1, 1] += 3  # BRCA1 nonsense
data[2, 2] += 3  # EGFR frameshift
data[3, 3] += 4  # KRAS splice

df = pd.DataFrame(data, index=variants, columns=genes)

# Gene function
gene_func = ['Tumor Suppressor']*4 + ['Oncogene']*4
func_palette = {'Tumor Suppressor': '#4927F5', 'Oncogene': '#F54927'}
col_colors = pd.Series(gene_func, index=genes).map(func_palette)

# Neon orange-yellow on light
neon_cmap = LinearSegmentedColormap.from_list('genomic', ['#f8fafc', '#4927F5', '#F54927', '#F5B027'])

g = sns.clustermap(df, cmap=neon_cmap, col_colors=col_colors,
                   method='average', metric='euclidean',
                   linewidths=0.4, linecolor='#e5e7eb',
                   figsize=(9, 8), dendrogram_ratio=(0.12, 0.12),
                   cbar_pos=(0.01, 0.08, 0.008, 0.12),
                   annot=True, fmt='.1f', annot_kws={'size': 8, 'color': '#1f2937'})

g.fig.patch.set_facecolor('#ffffff')
g.ax_heatmap.set_facecolor('#ffffff')
g.ax_heatmap.tick_params(colors='#1f2937', labelsize=8)
g.ax_row_dendrogram.set_facecolor('#ffffff')
g.ax_col_dendrogram.set_facecolor('#ffffff')
g.cax.tick_params(colors='#1f2937', labelsize=7)

g.fig.suptitle('Genomic Variant Impact', color='#1f2937', fontsize=13, fontweight='bold', y=1.02)
plt.show()