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Challenge

Build a Biopython Multiple Sequence Alignment Quality Scorer with Qdrant

Align homologous gene transcripts downloaded from public repositories and calculate pairwise distance matrices. Vectorize alignment features into Qdrant to detect anomalous outlier sequences.

Data ScienceHosted by Vera
Challenge brief

What you are building

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

Align homologous gene transcripts downloaded from public repositories and calculate pairwise distance matrices. Vectorize alignment features into Qdrant to detect anomalous outlier sequences.

Computational Biologist

Load homologous FASTA transcripts using Biopython SeqIO.

Compute gap frequencies and positional identity matrices across sequence collections.

Vectorize alignment summary profiles and index them in a local Qdrant collection.

Identify distance outliers and output quality warnings for human curator verification.

Streamlit app with interactive distance plots and outlier inspection tables.

Use Biopython test suite FASTA samples and public viral or eukaryotic homologous transcript sets. Starter examples below are synthetic. They are not downloaded records.

Biopython Employs Biopython's sequence analysis data structures to parse FASTA alignments and compute residue statistics.

qdrant, biopython, streamlit. Qdrant provides low-latency vector similarity search to cluster alignment score vectors and find outliers. Small local embedding model or tabular feature projector for alignment metric indexing.

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.

Parses multi-sequence FASTA files accurately using Biopython.

Calculates positional identity and indexes metric vectors into Qdrant.

Flags sequences with high gap penalties or divergent residue scores.

```json [ { "input": { "alignment_id": "ALN-101", "sequences": [ ">seqA\nATGCGATCG", ">seqB\nATGCGATCG", ">seqC\nATGCGATCA" ] }, "expected_output": { "alignment_id": "ALN-101", "consensus_identity": 0.963, "outliers_detected": 0, "status": "CONCORDANT" } }, { "input": { "alignment_id": "ALN-102", "sequences": [ ">seqA\nATGCGATCG", ">seqB\nNNNNGATCG", ">seqC\nATGCGATCG" ] }, "expected_output": { "alignment_id": "ALN-102", "consensus_identity": 0.667, "outliers_detected": 1, "status": "DISCORDANT_ALERT" } } ] ```

Standard sequence quality profiling tool operating exclusively on open synthetic or public FASTA data. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Standard sequence quality profiling tool operating exclusively on open synthetic or public FASTA data. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Parses multi-sequence FASTA files accurately using Biopython. Calculates positional identity and indexes metric vectors into Qdrant. Flags sequences with high gap penalties or divergent residue scores.

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

Load homologous FASTA transcripts using Biopython SeqIO. Compute gap frequencies and positional identity matrices across sequence collections. Vectorize alignment summary profiles and index them in a local Qdrant collection. Identify distance outliers and output quality warnings for human curator verification.

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

Parses multi-sequence FASTA files accurately using Biopython. Calculates positional identity and indexes metric vectors into Qdrant. Flags sequences with high gap penalties or divergent residue scores.

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

Streamlit app with interactive distance plots and outlier inspection tables.

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

Standard sequence quality profiling tool operating exclusively on open synthetic or public FASTA data.

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

  • Load homologous FASTA transcripts using Biopython SeqIO.

  • Compute gap frequencies and positional identity matrices across sequence collections.

  • Vectorize alignment summary profiles and index them in a local Qdrant collection.

  • Identify distance outliers and output quality warnings for human curator verification.

Resources and assets

Reference links and supporting material

Dataset notes

Use Biopython test suite FASTA samples and public viral or eukaryotic homologous transcript sets. 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.

Evaluation checks
  • Load homologous FASTA transcripts using Biopython SeqIO. Compute gap frequencies and positional identity ma...
  • Parses multi-sequence FASTA files accurately using Biopython. Calculates positional identity and indexes me...
  • Streamlit app with interactive distance plots and outlier inspection tables.
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

Action Space
  • Qdrant · Optional
Observation
  • 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

No recipe freeze time is recorded.

Frequently Asked Questions about Build a Biopython Multiple Sequence Alignment Quality Scorer with Qdrant