DockQvsCSPRank.py

import pandas as pd
import matplotlib.pyplot as plt

# Load data from CSPRANK.csv
data = pd.read_csv('/home/tiburon/Desktop/ROT4/CSP_Rank/CSPRANK.csv')

# Display the first few rows of the dataframe
print(data.head())
data['consensus_AF2-consensus'] = data['consensus_AF2'] - data['consensus_NMR']

# Create a figure with two subplots
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6))

# Plot a scatterplot of AF2_DockQ vs consensus_AF2-consensus on the first subplot
ax1.scatter(data['AF2_DockQ'], data['consensus_AF2-consensus'])
ax1.set_xlabel('DockQ')
ax1.set_ylabel('Δconsensus')
ax1.set_title('Scatterplot of DockQ vs Δconsensus')
ax1.axhline(y=0, color='red', linestyle='--')
ax1.text(0.5, 0.9, 'AF2 > PDB', color='red', fontsize=12, fontweight='bold', transform=ax1.transAxes, ha='center')
ax1.text(0.5, 0.1, 'PDB > AF2', color='red', fontsize=12, fontweight='bold', transform=ax1.transAxes, ha='center')

# Plot a scatterplot of AF2_TM vs consensus_AF2-consensus on the second subplot
ax2.scatter(data['AF2_TM'], data['consensus_AF2-consensus'])
ax2.set_xlabel('TM')
ax2.set_ylabel('Δconsensus')
ax2.set_title('Scatterplot of TM vs Δconsensus')
ax2.axhline(y=0, color='red', linestyle='--')
ax2.text(0.5, 0.9, 'AF2 > PDB', color='red', fontsize=12, fontweight='bold', transform=ax2.transAxes, ha='center')
ax2.text(0.5, 0.1, 'PDB > AF2', color='red', fontsize=12, fontweight='bold', transform=ax2.transAxes, ha='center')
# Save the figure
plt.tight_layout()
plt.savefig('./Figures/DockQ_vs_CSPRank.png')
plt.show()