predict_tissue_specific
Predicts how genetic variants affect gene regulation in specific tissues like brain, liver, and heart to identify tissue-specific disease mechanisms.
Instructions
Predict variant effects across multiple tissues.
Compares regulatory impact in different tissues to identify tissue-specific effects.
Default tissues: brain, liver, heart (customizable)
Returns impact levels and expression changes for each tissue.
Perfect for: understanding tissue-specific disease mechanisms, prioritizing relevant tissues.
Example: "Compare rs429358 effects in brain, liver, and heart"
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| chromosome | Yes | Chromosome | |
| position | Yes | Genomic position | |
| ref | Yes | Reference allele | |
| alt | Yes | Alternate allele | |
| tissues | No | List of tissues to test (default: brain, liver, heart) |
Implementation Reference
- scripts/alphagenome_bridge.py:297-321 (handler)Core handler function implementing predict_tissue_specific tool logic: iterates over tissues, calls predict_variant_effect for each, aggregates tissue-specific impact results.def predict_tissue_specific(client, params: Dict[str, Any]) -> Dict[str, Any]: """ Predict variant effects across multiple tissues. """ tissues = params.get('tissues', ['brain', 'liver', 'heart']) results = {} for tissue in tissues: tissue_params = params.copy() tissue_params['tissue_type'] = tissue try: result = predict_variant_effect(client, tissue_params) results[tissue] = { 'expression_impact': result['predictions'].get('rna_seq', {}).get('fold_change', 0), 'splice_impact': result['predictions'].get('splice', {}).get('delta', 0), 'impact_level': result['interpretation']['impact_level'] } except Exception as e: print(f"Warning: Failed to predict for tissue {tissue}: {e}", file=sys.stderr) results[tissue] = {'error': str(e)} return { 'variant': f"{params.get('chromosome')}:{params.get('position')}{params.get('ref')}>{params.get('alt')}", 'tissue_results': results }
- src/tools.ts:198-244 (schema)Tool schema definition including name, description, and inputSchema for validation (chromosome, position, ref, alt, optional tissues).export const PREDICT_TISSUE_SPECIFIC_TOOL: Tool = { name: 'predict_tissue_specific', description: `Predict variant effects across multiple tissues. Compares regulatory impact in different tissues to identify tissue-specific effects. Default tissues: brain, liver, heart (customizable) Returns impact levels and expression changes for each tissue. Perfect for: understanding tissue-specific disease mechanisms, prioritizing relevant tissues. Example: "Compare rs429358 effects in brain, liver, and heart"`, inputSchema: { type: 'object', properties: { chromosome: { type: 'string', description: 'Chromosome', pattern: '^chr([1-9]|1[0-9]|2[0-2]|X|Y)$', }, position: { type: 'number', description: 'Genomic position', minimum: 1, }, ref: { type: 'string', description: 'Reference allele', pattern: '^[ATGCatgc]+$', }, alt: { type: 'string', description: 'Alternate allele', pattern: '^[ATGCatgc]+$', }, tissues: { type: 'array', items: { type: 'string', }, description: 'List of tissues to test (default: brain, liver, heart)', }, }, required: ['chromosome', 'position', 'ref', 'alt'], }, };
- src/index.ts:154-158 (registration)MCP server handler registration: switch case dispatching to AlphaGenome client predictTissueSpecific method.case 'predict_tissue_specific': { const result = await getClient().predictTissueSpecific(args); return { content: [{ type: 'text', text: JSON.stringify(result, null, 2) }], };
- src/tools.ts:709-730 (registration)Tool registration in ALL_TOOLS array export, including PREDICT_TISSUE_SPECIFIC_TOOL (line 713).export const ALL_TOOLS: Tool[] = [ PREDICT_VARIANT_TOOL, BATCH_SCORE_TOOL, ASSESS_PATHOGENICITY_TOOL, PREDICT_TISSUE_SPECIFIC_TOOL, COMPARE_VARIANTS_TOOL, PREDICT_SPLICE_IMPACT_TOOL, PREDICT_EXPRESSION_IMPACT_TOOL, ANALYZE_GWAS_LOCUS_TOOL, COMPARE_ALLELES_TOOL, BATCH_TISSUE_COMPARISON_TOOL, PREDICT_TF_BINDING_IMPACT_TOOL, PREDICT_CHROMATIN_IMPACT_TOOL, COMPARE_PROTECTIVE_RISK_TOOL, BATCH_PATHOGENICITY_FILTER_TOOL, COMPARE_VARIANTS_SAME_GENE_TOOL, PREDICT_ALLELE_SPECIFIC_EFFECTS_TOOL, ANNOTATE_REGULATORY_CONTEXT_TOOL, BATCH_MODALITY_SCREEN_TOOL, GENERATE_VARIANT_REPORT_TOOL, EXPLAIN_VARIANT_IMPACT_TOOL, ];
- scripts/alphagenome_bridge.py:806-807 (registration)Python bridge dispatch: routes 'predict_tissue_specific' action to the handler function.elif action == 'predict_tissue_specific': result = predict_tissue_specific(client, params)