predict_tf_binding_impact

Analyze how genetic variants affect transcription factor binding sites using ChIP-seq predictions to identify regulatory changes.

Instructions

Focus on transcription factor binding effects only.

Analyzes TF binding site changes using ChIP-seq predictions.

Perfect for: TF binding site variants, regulatory element analysis.

Example: "Analyze TF binding impact of chr1:12345678G>A"

Input Schema

TableJSON Schema

Name	Required	Description	Default
`chromosome`	Yes
`position`	Yes
`ref`	Yes
`alt`	Yes
`tissue_type`	No

Implementation Reference

src/tools.ts:429-449 (schema)

Tool schema definition including input validation schema for predict_tf_binding_impact

export const PREDICT_TF_BINDING_IMPACT_TOOL: Tool = {
  name: 'predict_tf_binding_impact',
  description: `Focus on transcription factor binding effects only.

Analyzes TF binding site changes using ChIP-seq predictions.

Perfect for: TF binding site variants, regulatory element analysis.

Example: "Analyze TF binding impact of chr1:12345678G>A"`,
  inputSchema: {
    type: 'object',
    properties: {
      chromosome: { type: 'string', pattern: '^chr([1-9]|1[0-9]|2[0-2]|X|Y)$' },
      position: { type: 'number', minimum: 1 },
      ref: { type: 'string', pattern: '^[ATGCatgc]+$' },
      alt: { type: 'string', pattern: '^[ATGCatgc]+$' },
      tissue_type: { type: 'string' },
    },
    required: ['chromosome', 'position', 'ref', 'alt'],
  },
};

src/tools.ts:709-730 (registration)

Registration of predict_tf_binding_impact tool in the ALL_TOOLS array used by MCP server

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,
];

src/index.ts:205-211 (handler)

MCP server dispatch handler for predict_tf_binding_impact tool call

case 'predict_tf_binding_impact': {
  const params = validateInput(variantPredictionSchema, args) as VariantPredictionParams;
  const result = await getClient().predictTfBindingImpact(params);
  return {
    content: [{ type: 'text', text: JSON.stringify(result, null, 2) }],
  };
}

src/alphagenome-client.ts:352-358 (handler)

AlphaGenomeClient method that handles predict_tf_binding_impact by calling Python bridge

async predictTfBindingImpact(params: VariantPredictionParams): Promise<any> {
  try {
    return await this.callPythonBridge('predict_tf_binding_impact', params);
  } catch (error) {
    if (error instanceof ApiError) throw error;
    throw new ApiError(`TF binding impact prediction failed: ${error}`, 500);
  }

scripts/alphagenome_bridge.py:485-493 (handler)

Core Python handler implementing the predict_tf_binding_impact logic by specializing AlphaGenome predictions for TF binding

def predict_tf_binding_impact(client, params: Dict[str, Any]) -> Dict[str, Any]:
    """Focus on TF binding effects only."""
    params['output_types'] = [dna_client.OutputType.CHIP_TF]
    result = predict_variant_effect(client, params)
    return {
        'variant': result['variant'],
        'tf_binding': result['predictions'].get('tf_binding', []),
        'impact_level': result['interpretation']['impact_level']
    }

AlphaGenome MCP Server