Somatic Mutation Dosage RAG and Metastatic Tropism Agent using LlamaIndex
Clinical cancer interpretation requires mapping gene mutant dosages across tens of thousands of tumor samples to predict metastatic organ tropism. Build an advanced RAG agent using LlamaIndex to query somatic mutation databases and output high-confidence metastatic tropism predictions with 92% evaluation score accuracy.
What you are building
Develop an advanced genomic RAG system using LlamaIndex to map mutant dosage to metastatic organ tropism.
How work is evaluated
Evaluates RAG retrieval accuracy for predicting metastatic organ tropism based on somatic mutation dosage.
Datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
tropism_organ_validity
Verifies organ site belongs to standard clinical anatomical list.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
rag_eval_score
Evaluation score based on prediction correctness and retrieval context relevance. • target: 0.92 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Learning goals
Implement advanced retrieval-augmented generation (RAG) using LlamaIndex.
Index large-scale clinical cancer genomic datasets (60,000 sample cohort profiles).
Query somatic mutation dosage vectors to infer metastatic organ tropism probabilities.
Achieve 92% evaluation accuracy on metastatic target site prediction.
Resources
Synthetic somatic mutation dosage profiles across 60,000 tumor samples with associated organ tropism annotations.
Challenge setup
Evaluates RAG retrieval accuracy for predicting metastatic organ tropism based on somatic mutation dosage.
Challenge input
JSON containing somatic mutations and copy number/dosage ratios.
LlamaIndex
Leading framework for indexing and querying structured/unstructured enterprise data.
Evaluated output
JSON containing target_organ_tropism and confidence_score.
- Verifies organ site belongs to standard clinical anatomical list.
- Evaluation score based on prediction correctness and retrieval context relevance. • target: 0.92 • range: 0-1
- Benchmark: Oncology RAG & Tropism Prediction Benchmark
- Rag Eval Score target: 0.92
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
Shows the first task, up to three tools, and up to three evidence items.
View technical recipe
Configured tools
- Meta · Required
- Llama Index · Optional
- Testers AI · Optional
Evaluation contract
- tropism_organ_validity · Weight 1
- rag_eval_score · Weight 1
Metrics
- rag_eval_score · Target 0.92
Benchmarks
- Oncology RAG & Tropism Prediction Benchmark
- biotech
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON containing somatic mutations and copy number/dosage ratios.
Output: JSON containing target_organ_tropism and confidence_score.
Execution harness: Python
Evaluation tools
- LlamaIndex · Agent Framework
Recipe freeze marker
No recipe freeze time is recorded.