Initial commit

skills/gget/scripts/gene_analysis.py

@@ -0,0 +1,161 @@
+#!/usr/bin/env python3
+"""
+Gene Analysis Script
+Quick analysis of a gene: search, info, sequences, expression, and enrichment
+"""
+
+import argparse
+import sys
+import gget
+
+
+def analyze_gene(gene_name, species="homo_sapiens", output_prefix=None):
+    """
+    Perform comprehensive analysis of a gene.
+
+    Args:
+        gene_name: Gene symbol to analyze
+        species: Species name (default: homo_sapiens)
+        output_prefix: Prefix for output files (default: gene_name)
+    """
+    if output_prefix is None:
+        output_prefix = gene_name.lower()
+
+    print(f"Analyzing gene: {gene_name}")
+    print("=" * 60)
+
+    # Step 1: Search for the gene
+    print("\n1. Searching for gene...")
+    search_results = gget.search([gene_name], species=species, limit=1)
+
+    if len(search_results) == 0:
+        print(f"Error: Gene '{gene_name}' not found in {species}")
+        return False
+
+    gene_id = search_results["ensembl_id"].iloc[0]
+    print(f"   Found: {gene_id}")
+    print(f"   Description: {search_results['ensembl_description'].iloc[0]}")
+
+    # Step 2: Get detailed information
+    print("\n2. Getting detailed information...")
+    gene_info = gget.info([gene_id], pdb=True)
+    gene_info.to_csv(f"{output_prefix}_info.csv", index=False)
+    print(f"   Saved to: {output_prefix}_info.csv")
+
+    if "uniprot_id" in gene_info.columns and gene_info["uniprot_id"].iloc[0]:
+        print(f"   UniProt ID: {gene_info['uniprot_id'].iloc[0]}")
+    if "pdb_id" in gene_info.columns and gene_info["pdb_id"].iloc[0]:
+        print(f"   PDB IDs: {gene_info['pdb_id'].iloc[0]}")
+
+    # Step 3: Get sequences
+    print("\n3. Retrieving sequences...")
+    nucleotide_seq = gget.seq([gene_id])
+    protein_seq = gget.seq([gene_id], translate=True)
+
+    with open(f"{output_prefix}_nucleotide.fasta", "w") as f:
+        f.write(nucleotide_seq)
+    print(f"   Nucleotide sequence saved to: {output_prefix}_nucleotide.fasta")
+
+    with open(f"{output_prefix}_protein.fasta", "w") as f:
+        f.write(protein_seq)
+    print(f"   Protein sequence saved to: {output_prefix}_protein.fasta")
+
+    # Step 4: Get tissue expression
+    print("\n4. Getting tissue expression...")
+    try:
+        tissue_expr = gget.archs4(gene_name, which="tissue")
+        tissue_expr.to_csv(f"{output_prefix}_tissue_expression.csv", index=False)
+        print(f"   Saved to: {output_prefix}_tissue_expression.csv")
+
+        # Show top tissues
+        top_tissues = tissue_expr.nlargest(5, "median")
+        print("\n   Top expressing tissues:")
+        for _, row in top_tissues.iterrows():
+            print(f"     {row['tissue']}: median = {row['median']:.2f}")
+    except Exception as e:
+        print(f"   Warning: Could not retrieve ARCHS4 data: {e}")
+
+    # Step 5: Find correlated genes
+    print("\n5. Finding correlated genes...")
+    try:
+        correlated = gget.archs4(gene_name, which="correlation")
+        correlated.to_csv(f"{output_prefix}_correlated_genes.csv", index=False)
+        print(f"   Saved to: {output_prefix}_correlated_genes.csv")
+
+        # Show top correlated
+        print("\n   Top 10 correlated genes:")
+        for _, row in correlated.head(10).iterrows():
+            print(f"     {row['gene_symbol']}: r = {row['correlation']:.3f}")
+    except Exception as e:
+        print(f"   Warning: Could not retrieve correlation data: {e}")
+
+    # Step 6: Get disease associations
+    print("\n6. Getting disease associations...")
+    try:
+        diseases = gget.opentargets(gene_id, resource="diseases", limit=10)
+        diseases.to_csv(f"{output_prefix}_diseases.csv", index=False)
+        print(f"   Saved to: {output_prefix}_diseases.csv")
+
+        print("\n   Top 5 disease associations:")
+        for _, row in diseases.head(5).iterrows():
+            print(f"     {row['disease_name']}: score = {row['overall_score']:.3f}")
+    except Exception as e:
+        print(f"   Warning: Could not retrieve disease data: {e}")
+
+    # Step 7: Get drug associations
+    print("\n7. Getting drug associations...")
+    try:
+        drugs = gget.opentargets(gene_id, resource="drugs", limit=10)
+        if len(drugs) > 0:
+            drugs.to_csv(f"{output_prefix}_drugs.csv", index=False)
+            print(f"   Saved to: {output_prefix}_drugs.csv")
+            print(f"\n   Found {len(drugs)} drug associations")
+        else:
+            print("   No drug associations found")
+    except Exception as e:
+        print(f"   Warning: Could not retrieve drug data: {e}")
+
+    print("\n" + "=" * 60)
+    print("Analysis complete!")
+    print(f"\nOutput files (prefix: {output_prefix}):")
+    print(f"  - {output_prefix}_info.csv")
+    print(f"  - {output_prefix}_nucleotide.fasta")
+    print(f"  - {output_prefix}_protein.fasta")
+    print(f"  - {output_prefix}_tissue_expression.csv")
+    print(f"  - {output_prefix}_correlated_genes.csv")
+    print(f"  - {output_prefix}_diseases.csv")
+    print(f"  - {output_prefix}_drugs.csv (if available)")
+
+    return True
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Perform comprehensive analysis of a gene using gget"
+    )
+    parser.add_argument("gene", help="Gene symbol to analyze")
+    parser.add_argument(
+        "-s",
+        "--species",
+        default="homo_sapiens",
+        help="Species (default: homo_sapiens)",
+    )
+    parser.add_argument(
+        "-o", "--output", help="Output prefix for files (default: gene name)"
+    )
+
+    args = parser.parse_args()
+
+    try:
+        success = analyze_gene(args.gene, args.species, args.output)
+        sys.exit(0 if success else 1)
+    except KeyboardInterrupt:
+        print("\n\nAnalysis interrupted by user")
+        sys.exit(1)
+    except Exception as e:
+        print(f"\n\nError: {e}")
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()