bio-blast

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NCBI BLAST sequence similarity search using BioPython. Use when a user wants to run BLAST programmatically with blastn/blastp and retrieve results in JSON format.

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[Academic Research]

When & Why to Use This Skill

This Claude skill facilitates NCBI BLAST sequence similarity searches using BioPython, enabling automated analysis of DNA and protein sequences. It allows researchers to programmatically execute blastn or blastp queries, apply organism-specific filters, and retrieve structured results in JSON format, streamlining bioinformatics workflows and comparative genomics research.

Use Cases

  • Identifying unknown DNA or protein sequences by comparing them against global databases like GenBank or SwissProt.
  • Automating homology searches in comparative genomics to identify conserved sequences across different species.
  • Filtering sequence alignment results for specific organisms (e.g., Homo sapiens) to focus on relevant biological data.
  • Integrating BLAST search results directly into downstream data analysis pipelines using structured JSON output.
namebio-blast
description"NCBI BLAST sequence similarity search using BioPython. Use when a user wants to run BLAST programmatically with blastn/blastp and retrieve results in JSON format."
user_invocabletrue

BLAST Search

NCBI BLAST (Basic Local Alignment Search Tool) を BioPython で実行し、結果を JSON 形式で取得するスキルです。

Quick Start

Install

uv pip install biopython typer

Run with FASTA

python scripts/run_blast_biopython.py --fasta path/to/query.fasta

Run with raw sequence

python scripts/run_blast_biopython.py --sequence ATGCGATCG...

Restrict to organism (e.g., human)

python scripts/run_blast_biopython.py --fasta query.fasta --organism "Homo sapiens"

Protein BLAST

python scripts/run_blast_biopython.py --program blastp --database swissprot --sequence MTEYKLVVVG...

Save output

python scripts/run_blast_biopython.py --fasta query.fasta --output blast_results.json

Output Format

Results are returned in JSON format with the following structure:

{
  "query": "No definition line",
  "query_length": 99,
  "database": "core_nt",
  "num_hits": 10,
  "hits": [
    {
      "rank": 1,
      "accession": "NM_007294",
      "title": "Homo sapiens BRCA1 DNA repair associated (BRCA1), mRNA",
      "e_value": 4.35e-43,
      "bit_score": 179.82,
      "percent_identity": 100.0,
      "identities": 99,
      "align_length": 99,
      "gaps": 0,
      "query_start": 1,
      "query_end": 99,
      "subject_start": 1,
      "subject_end": 99
    }
  ]
}

Command-line Options

  • --program: BLAST program (blastn, blastp, blastx, tblastn, tblastx). Default: blastn
  • --database: BLAST database (nt, nr, refseq_rna, swissprot, etc.). Default: nt
  • --fasta: Path to FASTA file (single sequence only)
  • --sequence: Raw query sequence string
  • --organism: Restrict search to organism (e.g., "Homo sapiens")
  • --expect: E-value threshold. Default: 0.001
  • --hitlist-size: Maximum number of hits. Default: 10
  • --output: Output path for JSON results

Best Practices

  1. Save results - Don't re-run searches unnecessarily
  2. Set E-value threshold - Default 10 is too permissive; use 0.001-0.01
  3. Use gget for quick searches - Simpler API for single sequences
  4. Cache parsed data - Avoid re-parsing large XML files
  5. Handle rate limits - NCBI limits request frequency

BLAST vs BLAT

Aspect BLAST BLAT
Purpose Similarity search Genome mapping
Sensitivity High Medium
Speed Medium Very fast
Best for Homolog search Position finding