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Challenge

Build a Gene Data Package FASTA Cleanser and Telemetry Monitor

Process multi-FASTA gene packages to detect non-IUPAC nucleotide characters and low-complexity repeats. Track data cleansing performance and error drift using Langfuse.

Data ScienceHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Process multi-FASTA gene packages to detect non-IUPAC nucleotide characters and low-complexity repeats. Track data cleansing performance and error drift using Langfuse.

Bioinformatics Pipeline Engineer

Stream multi-FASTA files from NCBI Datasets gene archives using Biopython SeqIO.

Scan each sequence entry for non-IUPAC nucleotide symbols, masked N-stretches, and degenerate codons.

Log cleaning latency, token counts, and sequence anomaly rates into Langfuse telemetry spans.

Export sanitized FASTA output alongside a structured data cleaning audit log.

Command-line pipeline configured with environment variables sending real-time telemetry to Langfuse UI.

Generate synthetic multi-FASTA files containing random mutations, non-IUPAC characters, and poly-N stretches. Starter examples below are synthetic. They are not downloaded records.

Biopython Employs Biopython's Bio.SeqIO and sequence validation routines to inspect sequence headers and character contents.

langfuse, biopython, pydantic. Langfuse provides observability, trace tracking, and latency metrics for repetitive data curation pipelines. Local or hosted LLM for generating contextual summaries of sequence anomaly clusters.

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.

Correctly identifies non-standard IUPAC characters (e.g. 'Z', '?', numbers) in input FASTA records.

Sends telemetry traces to Langfuse containing sequence identifier and processing duration.

Generates sanitized FASTA files preserving sequence IDs and valid biological characters.

```json [ { "input": { "record_id": "TRANS_001", "raw_sequence": "ATGCGTACNNNGTACG" }, "expected_output": { "valid_iupac": true, "n_ratio": 0.1875, "sanitized_sequence": "ATGCGTACNNNGTACG", "telemetry_logged": true } }, { "input": { "record_id": "TRANS_002", "raw_sequence": "ATGC123GZZTAG" }, "expected_output": { "valid_iupac": false, "invalid_characters": [ "1", "2", "3", "Z" ], "sanitized_sequence": "ATGCGGTAG", "telemetry_logged": true } } ] ```

Processes pure nucleotide strings from public or synthetic data without clinical patient associations. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Processes pure nucleotide strings from public or synthetic data without clinical patient associations. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Correctly identifies non-standard IUPAC characters (e.g. 'Z', '?', numbers) in input FASTA records. Sends telemetry traces to Langfuse containing sequence identifier and processing duration. Generates sanitized FASTA files preserving sequence IDs and valid biological characters.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Stream multi-FASTA files from NCBI Datasets gene archives using Biopython SeqIO. Scan each sequence entry for non-IUPAC nucleotide symbols, masked N-stretches, and degenerate codons. Log cleaning latency, token counts, and sequence anomaly rates into Langfuse telemetry spans. Export sanitized FASTA output alongside a structured data cleaning audit log.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Correctly identifies non-standard IUPAC characters (e.g. 'Z', '?', numbers) in input FASTA records. Sends telemetry traces to Langfuse containing sequence identifier and processing duration. Generates sanitized FASTA files preserving sequence IDs and valid biological characters.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Command-line pipeline configured with environment variables sending real-time telemetry to Langfuse UI.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Processes pure nucleotide strings from public or synthetic data without clinical patient associations.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Stream multi-FASTA files from NCBI Datasets gene archives using Biopython SeqIO.

  • Scan each sequence entry for non-IUPAC nucleotide symbols, masked N-stretches, and degenerate codons.

  • Log cleaning latency, token counts, and sequence anomaly rates into Langfuse telemetry spans.

  • Export sanitized FASTA output alongside a structured data cleaning audit log.

Resources and assets

Reference links and supporting material

Dataset notes

Generate synthetic multi-FASTA files containing random mutations, non-IUPAC characters, and poly-N stretches. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

Langfuse

Open-source LLM observability and evals.

Evaluated output

No output checks are configured.

Evaluation checks
  • Stream multi-FASTA files from NCBI Datasets gene archives using Biopython SeqIO. Scan each sequence entry f...
  • Correctly identifies non-standard IUPAC characters (e.g. 'Z', '?', numbers) in input FASTA records. Sends t...
  • Command-line pipeline configured with environment variables sending real-time telemetry to Langfuse UI.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 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.

View technical recipe

Configured tools

Observation
  • Langfuse · Optional
Reward / Eval
  • Langfuse · 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

No recipe freeze time is recorded.

Frequently Asked Questions about Build a Gene Data Package FASTA Cleanser and Telemetry Monitor