Agent Skills › Runchuan-BU/BioClaw › blast-search

blast-search

GitHub

执行BLAST序列相似性搜索，支持本地和远程NCBI数据库查询。用于比对DNA/RNA/蛋白质序列、识别未知序列或查找同源序列，并提供结果分析与后续建议。

container/skills/blast-search/SKILL.md Runchuan-BU/BioClaw

触发场景

用户询问BLAST相关操作需要查找序列相似性或进行同源性分析要求识别特定基因或蛋白质序列

安装

npx skills add Runchuan-BU/BioClaw --skill blast-search -g -y

更多选项

非标准路径

npx skills add https://github.com/Runchuan-BU/BioClaw/tree/main/container/skills/blast-search -g -y

不安装直接使用

npx skills use Runchuan-BU/BioClaw@blast-search

指定 Agent (Claude Code)

npx skills add Runchuan-BU/BioClaw --skill blast-search -a claude-code -g -y

安装 repo 全部 skill

npx skills add Runchuan-BU/BioClaw --all -g -y

预览 repo 内 skill

npx skills add Runchuan-BU/BioClaw --list

SKILL.md

Frontmatter

{
    "name": "blast-search",
    "description": "Run BLAST sequence similarity searches. Use when the user asks to BLAST a sequence, find similar sequences, identify a gene\/protein, or do homology search. Triggers on \"blast\", \"sequence similarity\", \"homology\", \"identify sequence\"."
}

BLAST Search

Run NCBI BLAST+ searches inside the BioClaw container.

When to Use

User provides a DNA/RNA/protein sequence and wants to find similar sequences
User asks to identify an unknown sequence
User wants to check sequence conservation across species

How to Execute

1. Determine BLAST program

Input	Database	Program
Nucleotide query	Nucleotide DB	`blastn`
Protein query	Protein DB	`blastp`
Nucleotide query	Protein DB	`blastx`
Protein query	Nucleotide DB	`tblastn`

2. For local BLAST (sequences provided by user)

# Create query file
cat > /tmp/query.fa << 'EOF'
>query_sequence
ATGCGATCGATCGATCG...
EOF

# Create subject file (if user provides reference)
cat > /tmp/subject.fa << 'EOF'
>reference
ATGCGATCGATCGATCG...
EOF

# Run BLAST
blastn -query /tmp/query.fa -subject /tmp/subject.fa -outfmt 6 -evalue 1e-5

3. For remote BLAST (against NCBI databases)

Use BioPython's NCBIWWW module:

from Bio.Blast import NCBIWWW, NCBIXML
from Bio import SeqIO

# Read sequence
sequence = "ATGCGATCGATCGATCG..."

# Run remote BLAST
result_handle = NCBIWWW.qblast("blastn", "nt", sequence)
blast_records = NCBIXML.parse(result_handle)

for record in blast_records:
    for alignment in record.alignments[:10]:
        print(f"Title: {alignment.title}")
        for hsp in alignment.hsps:
            print(f"  Score: {hsp.score}, E-value: {hsp.expect}")
            print(f"  Identity: {hsp.identities}/{hsp.align_length} ({hsp.identities/hsp.align_length*100:.1f}%)")

4. Output format

Present results in a clear table:

*BLAST Results (top 10 hits)*

• Hit 1: Homo sapiens TP53 gene (98.5% identity, E=1e-45)
• Hit 2: Mus musculus Trp53 gene (89.2% identity, E=1e-38)
...