Sequence Alignment#

A skill for performing sequence alignment using NCBI BLAST API. Supports nucleotide and protein sequence comparison against major biological databases.

When to Use#

• Use this skill when the task needs performing sequence alignment using NCBI BLAST API. Supports nucleotide and protein sequence comparison against major biological databases.
• Use this skill for data analysis tasks that require explicit assumptions, bounded scope, and a reproducible output format.
• Use this skill when the response must stay inside the documented task boundary instead of expanding into adjacent work.

Key Features#

See ## Features above for related details.

• Scope-focused workflow aligned to: A skill for performing sequence alignment using NCBI BLAST API. Supports nucleotide and protein sequence comparison against major biological databases.
• Packaged executable path(s): scripts/main.py.
• Reference material available in references/ for task-specific guidance.
• Structured execution path designed to keep outputs consistent and reviewable.

Dependencies#

See ## Prerequisites above for related details.

• Python: 3.10+. Repository baseline for current packaged skills.
• Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.

Example Usage#

See ## Usage above for related details.

bash

cd "20260318/scientific-skills/Data Analytics/sequence-alignment"
python -m py_compile scripts/main.py
python scripts/main.py --help

Example run plan:

1. Confirm the user input, output path, and any required config values.
2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
3. Run python scripts/main.py with the validated inputs.
4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details#

See ## Workflow above for related details.

• Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
• Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
• Primary implementation surface: scripts/main.py.
• Reference guidance: references/ contains supporting rules, prompts, or checklists.
• Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
• Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.

Quick Check#

Use this command to verify that the packaged script entry point can be parsed before deeper execution.

bash

python -m py_compile scripts/main.py

Audit-Ready Commands#

Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.

bash

python -m py_compile scripts/main.py
python scripts/main.py --help

Workflow#

1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

Features#

• BLAST API Integration: Query NCBI BLAST service for sequence similarity search
• Multiple BLAST Programs: blastn, blastp, blastx, tblastn, tblastx
• Alignment Visualization: Display results in human-readable format
• Database Support: nr, nt, swissprot, refseq, pdb, and more

Usage#

text

python scripts/main.py --sequence "ATGCGTACGTAGCTAGCTAG" --program blastn --database nt --output results.txt

Parameters#

ParameterDescriptionRequired--sequenceQuery sequence (DNA/Protein)Yes--programBLAST program: blastn, blastp, blastx, tblastn, tblastxYes--databaseTarget database: nr, nt, swissprot, pdb, refseq_proteinYes--outputOutput file pathNo--formatOutput format: text, json, csvNo (default: text)--max_hitsMaximum number of hits to returnNo (default: 10)--evalueE-value thresholdNo (default: 10)

Technical Difficulty#

Medium - Requires understanding of BLAST algorithm, API handling with retry logic, and biological sequence formats.

BLAST Programs Reference#

ProgramQuery TypeDatabase TypeUse CaseblastnNucleotideNucleotideDNA vs DNAblastpProteinProteinProtein vs ProteinblastxNucleotide (translated)ProteinDNA vs ProteintblastnProteinNucleotide (translated)Protein vs DNAtblastxNucleotide (translated)Nucleotide (translated)Translated DNA vs DNA

Example Workflows#

DNA Sequence Similarity Search#

text

python scripts/main.py --sequence "ATGGCCCTGTGGATGCGCTTCTTAGTCG" --program blastn --database nt --max_hits 5

Protein Sequence Alignment#

text

python scripts/main.py --sequence "MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQAPILSRVGDGT" --program blastp --database swissprot --evalue 0.001

Output Format#

Results include:

• Query sequence info
• Hit definitions and accession numbers
• Alignment scores (bit score, e-value)
• Percent identity and similarity
• Alignment visualization with match/mismatch highlighting

References#

• BLAST Documentation
• NCBI BLAST API Guide

Risk Assessment#

Risk IndicatorAssessmentLevelCode ExecutionPython scripts with toolsHighNetwork AccessExternal API callsHighFile System AccessRead/write dataMediumInstruction TamperingStandard prompt guidelinesLowData ExposureData handled securelyMedium

Security Checklist#

• No hardcoded credentials or API keys
• No unauthorized file system access (../)
• Output does not expose sensitive information
• Prompt injection protections in place
• API requests use HTTPS only
• Input validated against allowed patterns
• API timeout and retry mechanisms implemented
• Output directory restricted to workspace
• Script execution in sandboxed environment
• Error messages sanitized (no internal paths exposed)
• Dependencies audited
• No exposure of internal service architecture

Prerequisites#

No additional Python packages required.

Evaluation Criteria#

Success Metrics#

• Successfully executes main functionality
• Output meets quality standards
• Handles edge cases gracefully
• Performance is acceptable

Test Cases#

1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status#

• Current Stage: Draft

• Next Review Date: 2026-03-06

• Known Issues: None

• Planned Improvements:

  • Performance optimization
  • Additional feature support

Output Requirements#

Every final response should make these items explicit when they are relevant:

• Objective or requested deliverable
• Inputs used and assumptions introduced
• Workflow or decision path
• Core result, recommendation, or artifact
• Constraints, risks, caveats, or validation needs
• Unresolved items and next-step checks

Error Handling#

• If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
• If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
• If scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.
• Do not fabricate files, citations, data, search results, or execution outcomes.

Input Validation#

This skill accepts requests that match the documented purpose of sequence-alignment and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

sequence-alignment only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

Response Template#

Use the following fixed structure for non-trivial requests:

1. Objective
2. Inputs Received
3. Assumptions
4. Workflow
5. Deliverable
6. Risks and Limits
7. Next Checks

If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.