mirror of
https://github.com/K-Dense-AI/claude-scientific-skills.git
synced 2026-01-26 16:58:56 +08:00
Initial commit
This commit is contained in:
Timothy Kassis
205
scientific-packages/arboreto/scripts/compare_algorithms.py
Normal file
205
scientific-packages/arboreto/scripts/compare_algorithms.py
Normal file
@@ -0,0 +1,205 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Compare GRNBoost2 and GENIE3 algorithms on the same dataset.
|
||||
|
||||
This script runs both algorithms on the same expression data and compares:
|
||||
- Runtime
|
||||
- Number of predicted links
|
||||
- Top predicted relationships
|
||||
- Overlap between predictions
|
||||
|
||||
Usage:
|
||||
python compare_algorithms.py <expression_file> [options]
|
||||
|
||||
Example:
|
||||
python compare_algorithms.py expression_data.tsv -t tf_names.txt
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import time
|
||||
import pandas as pd
|
||||
from arboreto.algo import grnboost2, genie3
|
||||
from arboreto.utils import load_tf_names
|
||||
|
||||
|
||||
def compare_networks(network1, network2, name1, name2, top_n=100):
|
||||
"""Compare two inferred networks."""
|
||||
print(f"\n{'='*60}")
|
||||
print("Network Comparison")
|
||||
print(f"{'='*60}")
|
||||
|
||||
# Basic statistics
|
||||
print(f"\n{name1} Statistics:")
|
||||
print(f" Total links: {len(network1)}")
|
||||
print(f" Unique TFs: {network1['TF'].nunique()}")
|
||||
print(f" Unique targets: {network1['target'].nunique()}")
|
||||
print(f" Importance range: [{network1['importance'].min():.3f}, {network1['importance'].max():.3f}]")
|
||||
|
||||
print(f"\n{name2} Statistics:")
|
||||
print(f" Total links: {len(network2)}")
|
||||
print(f" Unique TFs: {network2['TF'].nunique()}")
|
||||
print(f" Unique targets: {network2['target'].nunique()}")
|
||||
print(f" Importance range: [{network2['importance'].min():.3f}, {network2['importance'].max():.3f}]")
|
||||
|
||||
# Compare top predictions
|
||||
print(f"\nTop {top_n} Predictions Overlap:")
|
||||
|
||||
# Create edge sets for top N predictions
|
||||
top_edges1 = set(
|
||||
zip(network1.head(top_n)['TF'], network1.head(top_n)['target'])
|
||||
)
|
||||
top_edges2 = set(
|
||||
zip(network2.head(top_n)['TF'], network2.head(top_n)['target'])
|
||||
)
|
||||
|
||||
# Calculate overlap
|
||||
overlap = top_edges1 & top_edges2
|
||||
only_net1 = top_edges1 - top_edges2
|
||||
only_net2 = top_edges2 - top_edges1
|
||||
|
||||
overlap_pct = (len(overlap) / top_n) * 100
|
||||
|
||||
print(f" Shared edges: {len(overlap)} ({overlap_pct:.1f}%)")
|
||||
print(f" Only in {name1}: {len(only_net1)}")
|
||||
print(f" Only in {name2}: {len(only_net2)}")
|
||||
|
||||
# Show some example overlapping edges
|
||||
if overlap:
|
||||
print(f"\nExample overlapping predictions:")
|
||||
for i, (tf, target) in enumerate(list(overlap)[:5], 1):
|
||||
print(f" {i}. {tf} -> {target}")
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(
|
||||
description='Compare GRNBoost2 and GENIE3 algorithms'
|
||||
)
|
||||
parser.add_argument(
|
||||
'expression_file',
|
||||
help='Path to expression data file (TSV/CSV format)'
|
||||
)
|
||||
parser.add_argument(
|
||||
'-t', '--tf-file',
|
||||
help='Path to file containing transcription factor names (one per line)',
|
||||
default=None
|
||||
)
|
||||
parser.add_argument(
|
||||
'--grnboost2-output',
|
||||
help='Output file path for GRNBoost2 results',
|
||||
default='grnboost2_network.tsv'
|
||||
)
|
||||
parser.add_argument(
|
||||
'--genie3-output',
|
||||
help='Output file path for GENIE3 results',
|
||||
default='genie3_network.tsv'
|
||||
)
|
||||
parser.add_argument(
|
||||
'-s', '--seed',
|
||||
type=int,
|
||||
help='Random seed for reproducibility',
|
||||
default=42
|
||||
)
|
||||
parser.add_argument(
|
||||
'--sep',
|
||||
help='Separator for input file (default: tab)',
|
||||
default='\t'
|
||||
)
|
||||
parser.add_argument(
|
||||
'--transpose',
|
||||
action='store_true',
|
||||
help='Transpose the expression matrix (use if genes are rows)'
|
||||
)
|
||||
parser.add_argument(
|
||||
'--top-n',
|
||||
type=int,
|
||||
help='Number of top predictions to compare (default: 100)',
|
||||
default=100
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
# Load expression data
|
||||
print(f"Loading expression data from {args.expression_file}...")
|
||||
expression_data = pd.read_csv(args.expression_file, sep=args.sep, index_col=0)
|
||||
|
||||
# Transpose if needed
|
||||
if args.transpose:
|
||||
print("Transposing expression matrix...")
|
||||
expression_data = expression_data.T
|
||||
|
||||
print(f"Expression data shape: {expression_data.shape}")
|
||||
print(f" Observations (rows): {expression_data.shape[0]}")
|
||||
print(f" Genes (columns): {expression_data.shape[1]}")
|
||||
|
||||
# Load TF names if provided
|
||||
tf_names = None
|
||||
if args.tf_file:
|
||||
print(f"Loading transcription factor names from {args.tf_file}...")
|
||||
tf_names = load_tf_names(args.tf_file)
|
||||
print(f" Found {len(tf_names)} transcription factors")
|
||||
else:
|
||||
print("No TF file provided. Using all genes as potential regulators.")
|
||||
|
||||
# Run GRNBoost2
|
||||
print("\n" + "="*60)
|
||||
print("Running GRNBoost2...")
|
||||
print("="*60)
|
||||
start_time = time.time()
|
||||
|
||||
grnboost2_network = grnboost2(
|
||||
expression_data=expression_data,
|
||||
tf_names=tf_names,
|
||||
seed=args.seed
|
||||
)
|
||||
|
||||
grnboost2_time = time.time() - start_time
|
||||
print(f"GRNBoost2 completed in {grnboost2_time:.2f} seconds")
|
||||
|
||||
# Save GRNBoost2 results
|
||||
grnboost2_network.to_csv(args.grnboost2_output, sep='\t', index=False)
|
||||
print(f"Results saved to {args.grnboost2_output}")
|
||||
|
||||
# Run GENIE3
|
||||
print("\n" + "="*60)
|
||||
print("Running GENIE3...")
|
||||
print("="*60)
|
||||
start_time = time.time()
|
||||
|
||||
genie3_network = genie3(
|
||||
expression_data=expression_data,
|
||||
tf_names=tf_names,
|
||||
seed=args.seed
|
||||
)
|
||||
|
||||
genie3_time = time.time() - start_time
|
||||
print(f"GENIE3 completed in {genie3_time:.2f} seconds")
|
||||
|
||||
# Save GENIE3 results
|
||||
genie3_network.to_csv(args.genie3_output, sep='\t', index=False)
|
||||
print(f"Results saved to {args.genie3_output}")
|
||||
|
||||
# Compare runtimes
|
||||
print("\n" + "="*60)
|
||||
print("Runtime Comparison")
|
||||
print("="*60)
|
||||
print(f"GRNBoost2: {grnboost2_time:.2f} seconds")
|
||||
print(f"GENIE3: {genie3_time:.2f} seconds")
|
||||
speedup = genie3_time / grnboost2_time
|
||||
print(f"Speedup: {speedup:.2f}x (GRNBoost2 is {speedup:.2f}x faster)")
|
||||
|
||||
# Compare networks
|
||||
compare_networks(
|
||||
grnboost2_network,
|
||||
genie3_network,
|
||||
"GRNBoost2",
|
||||
"GENIE3",
|
||||
top_n=args.top_n
|
||||
)
|
||||
|
||||
print("\n" + "="*60)
|
||||
print("Comparison complete!")
|
||||
print("="*60)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
Reference in New Issue
Block a user