Build a Biopython Multiple Alignment Outlier Detector with Qdrant
Compute pairwise distance vectors across homologous transcripts and index representations into Qdrant. Flag outlier sequences and output FHIR DiagnosticReport payloads for biocuration teams.
What you are building
The core problem, expected build, and operating context for this challenge.
Compute pairwise distance vectors across homologous transcripts and index representations into Qdrant. Flag outlier sequences and output FHIR DiagnosticReport payloads for biocuration teams.
Phylogenomics Analyst
Align homologous transcript sets using Biopython multiple sequence alignment utilities.
Extract k-mer frequency vectors and alignment distance scores for each sequence record.
Index sequence feature embeddings into Qdrant vector collections to calculate centroid distances.
Flag distance outliers and assemble FHIR DiagnosticReport payloads highlighting anomalous accessions.
Interactive dashboard showing scatter-plot cluster distributions and downloadable outlier reports.
Fetch synthetic eukaryotic gene packages for ACRV1 and homologous vertebrate loci from mock data stores. Starter examples below are synthetic. They are not downloaded records.
Biopython Applies Biopython multiple alignment parsing and sequence distance calculation routines documented in README.
qdrant, biopython, fastapi. Stores high-dimensional k-mer vectors and performs cosine distance queries to detect structural sequence outliers. Fast remote LLM for summarizing cluster anomalies and framing curator review notes.
Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.
Computes k-mer frequency vectors from Biopython alignment sequences.
Stores and queries vector embeddings in a local or remote Qdrant collection.
Identifies sequences that deviate beyond two standard deviations from cluster centroids.
```json [ { "input": { "dataset_id": "HOM_GRP_10", "sequences": [ { "id": "TRANS_A", "seq": "ATGCGATCGATCGATC" }, { "id": "TRANS_B", "seq": "ATGCGATCGATCGATC" }, { "id": "TRANS_OUTLIER", "seq": "TTTTTTTTTTTTTTTT" } ] }, "expected_output": { "dataset_id": "HOM_GRP_10", "total_sequences": 3, "outliers_detected": [ "TRANS_OUTLIER" ], "cluster_centroid_distance": 0.89, "fhir_report_generated": true } }, { "input": { "dataset_id": "HOM_GRP_11", "sequences": [ { "id": "TRANS_1", "seq": "ATGGCTAGCTAG" }, { "id": "TRANS_2", "seq": "ATGGCTAGCTAG" } ] }, "expected_output": { "dataset_id": "HOM_GRP_11", "total_sequences": 2, "outliers_detected": [], "cluster_centroid_distance": 0, "fhir_report_generated": true } } ] ```
Research-only sequence clustering; completely separate from patient diagnostic testing. Use mock external writes. Require human review before any real deployment.
Participation guide
Research-only sequence clustering; completely separate from patient diagnostic testing. Use mock external writes and human review.
How work is evaluated
Computes k-mer frequency vectors from Biopython alignment sequences. Stores and queries vector embeddings in a local or remote Qdrant collection. Identifies sequences that deviate beyond two standard deviations from cluster centroids.
Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Complete workflow
Align homologous transcript sets using Biopython multiple sequence alignment utilities. Extract k-mer frequency vectors and alignment distance scores for each sequence record. Index sequence feature embeddings into Qdrant vector collections to calculate centroid distances. Flag distance outliers and assemble FHIR DiagnosticReport payloads highlighting anomalous accessions.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
Computes k-mer frequency vectors from Biopython alignment sequences. Stores and queries vector embeddings in a local or remote Qdrant collection. Identifies sequences that deviate beyond two standard deviations from cluster centroids.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
Interactive dashboard showing scatter-plot cluster distributions and downloadable outlier reports.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Research-only sequence clustering; completely separate from patient diagnostic testing.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Align homologous transcript sets using Biopython multiple sequence alignment utilities.
Extract k-mer frequency vectors and alignment distance scores for each sequence record.
Index sequence feature embeddings into Qdrant vector collections to calculate centroid distances.
Flag distance outliers and assemble FHIR DiagnosticReport payloads highlighting anomalous accessions.
Reference links and supporting material
Fetch synthetic eukaryotic gene packages for ACRV1 and homologous vertebrate loci from mock data stores. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Configuration summary for this challenge.
Challenge input
Input details are not configured.
Qdrant
Open-source vector database.
Evaluated output
No output checks are configured.
- Align homologous transcript sets using Biopython multiple sequence alignment utilities. Extract k-mer frequ...
- Computes k-mer frequency vectors from Biopython alignment sequences. Stores and queries vector embeddings i...
- Interactive dashboard showing scatter-plot cluster distributions and downloadable outlier reports.
- 2 public reference cases
- 2 configured tools
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
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Configured tools
- Qdrant · Optional
- Qdrant · Optional
Evaluation contract
- Complete workflow · Weight 40
- Correctness and evidence · Weight 30
- Review interface · Weight 20
- Safe execution · Weight 10
Reference cases
- 2 public reference cases
Workflow tasks
No workflow tasks are configured.
Recipe freeze marker
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