Agent skill

bio-local-blast

Run local BLAST searches using BLAST+ command-line tools. Use when running fast unlimited searches, building custom databases, performing large-scale analysis, or when NCBI servers are slow or unavailable.

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/local-blast

SKILL.md

Local BLAST

Run BLAST searches locally using NCBI BLAST+ command-line tools.

Installation

bash
# macOS
brew install blast

# Ubuntu/Debian
sudo apt install ncbi-blast+

# conda
conda install -c bioconda blast

# Verify installation
blastn -version

BLAST+ Programs

Command Query Database Description
blastn DNA DNA Nucleotide-nucleotide
blastp Protein Protein Protein-protein
blastx DNA Protein Translated query vs protein
tblastn Protein DNA Protein vs translated DB
tblastx DNA DNA Translated vs translated
makeblastdb - - Create BLAST database

Creating BLAST Databases

makeblastdb - Create Database

bash
# Create nucleotide database
makeblastdb -in sequences.fasta -dbtype nucl -out my_db

# Create protein database
makeblastdb -in proteins.fasta -dbtype prot -out my_proteins

# With title and parse sequence IDs
makeblastdb -in sequences.fasta -dbtype nucl -out my_db \
    -title "My Reference Database" -parse_seqids

Key Options:

Option Description Values
-in Input FASTA file Path
-dbtype Database type nucl, prot
-out Output database name Path prefix
-title Database title String
-parse_seqids Enable ID-based retrieval Flag
-taxid Assign taxonomy ID Integer
-taxid_map Taxonomy ID mapping file Path

Database Files Created

my_db.nhr  # Header file (nucl) / .phr (prot)
my_db.nin  # Index file (nucl) / .pin (prot)
my_db.nsq  # Sequence file (nucl) / .psq (prot)
my_db.ndb  # Alias file (optional)
my_db.not  # ID index (if parse_seqids)
my_db.ntf  # Index (if parse_seqids)
my_db.nto  # Index (if parse_seqids)

Running BLAST Searches

Basic Usage

bash
# BLASTN
blastn -query query.fasta -db my_db -out results.txt

# BLASTP
blastp -query proteins.fasta -db my_proteins -out results.txt

# BLASTX (translate query, search protein DB)
blastx -query genes.fasta -db nr -out results.txt

Common Options

Option Description Example
-query Query FASTA file -query seq.fa
-db Database name -db nt
-out Output file -out results.txt
-outfmt Output format -outfmt 6
-evalue E-value threshold -evalue 1e-5
-num_threads CPU threads -num_threads 8
-max_target_seqs Max hits -max_target_seqs 100
-max_hsps Max HSPs per hit -max_hsps 1
-word_size Word size -word_size 11
-dust Filter low complexity (nucl) -dust yes
-seg Filter low complexity (prot) -seg yes

Output Formats (-outfmt)

Value Format
0 Pairwise (default)
1 Query-anchored with identities
5 BLAST XML
6 Tabular
7 Tabular with comments
10 CSV

Tabular Output Fields (-outfmt 6)

Default columns: qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore

Custom columns:

bash
blastn -query query.fa -db my_db -outfmt "6 qseqid sseqid pident length evalue stitle"

Available Fields:

Field Description
qseqid Query ID
sseqid Subject ID
pident Percent identity
length Alignment length
mismatch Mismatches
gapopen Gap openings
qstart Query start
qend Query end
sstart Subject start
send Subject end
evalue E-value
bitscore Bit score
stitle Subject title
qcovs Query coverage
qcovhsp Query coverage per HSP

Code Patterns

Create Database and Search

bash
#!/bin/bash
# Create database from reference sequences
makeblastdb -in reference.fasta -dbtype nucl -out ref_db -parse_seqids

# Run BLAST
blastn -query query.fasta -db ref_db -out results.txt \
    -outfmt 6 -evalue 1e-10 -num_threads 4

# View results
head results.txt

BLAST with Tabular Output

bash
#!/bin/bash
blastn -query query.fasta -db my_db \
    -outfmt "6 qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore stitle" \
    -evalue 1e-5 \
    -max_target_seqs 10 \
    -num_threads 8 \
    -out results.tsv

Filter and Sort Results

bash
# Get hits with >90% identity
awk -F'\t' '$3 >= 90' results.tsv

# Sort by E-value
sort -t$'\t' -k11 -g results.tsv

# Get best hit per query
sort -t$'\t' -k1,1 -k11,11g results.tsv | sort -t$'\t' -k1,1 -u

Batch BLAST Multiple Files

bash
#!/bin/bash
for query_file in queries/*.fasta; do
    base=$(basename "$query_file" .fasta)
    echo "Processing $base..."

    blastn -query "$query_file" -db my_db \
        -outfmt 6 -evalue 1e-5 -num_threads 4 \
        -out "results/${base}_blast.tsv"
done

Python Wrapper

python
import subprocess
import os

def make_blast_db(fasta_file, db_name, db_type='nucl'):
    cmd = ['makeblastdb', '-in', fasta_file, '-dbtype', db_type, '-out', db_name, '-parse_seqids']
    subprocess.run(cmd, check=True)

def run_blast(query, db, output, program='blastn', evalue=1e-5, threads=4, outfmt=6):
    cmd = [program, '-query', query, '-db', db, '-out', output,
           '-outfmt', str(outfmt), '-evalue', str(evalue), '-num_threads', str(threads)]
    subprocess.run(cmd, check=True)

def parse_blast_tabular(filename):
    columns = ['qseqid', 'sseqid', 'pident', 'length', 'mismatch', 'gapopen',
               'qstart', 'qend', 'sstart', 'send', 'evalue', 'bitscore']
    hits = []
    with open(filename) as f:
        for line in f:
            values = line.strip().split('\t')
            hit = dict(zip(columns, values))
            hit['pident'] = float(hit['pident'])
            hit['evalue'] = float(hit['evalue'])
            hit['length'] = int(hit['length'])
            hits.append(hit)
    return hits

# Example usage
make_blast_db('reference.fasta', 'ref_db')
run_blast('query.fasta', 'ref_db', 'results.tsv')
hits = parse_blast_tabular('results.tsv')
for hit in hits[:5]:
    print(f"{hit['qseqid']} -> {hit['sseqid']}: {hit['pident']}% identity, E={hit['evalue']}")

Reciprocal Best BLAST

bash
#!/bin/bash
# Forward BLAST: A vs B
blastp -query species_A.fasta -db species_B_db -outfmt 6 -evalue 1e-5 \
    -max_target_seqs 1 -out A_vs_B.tsv

# Reverse BLAST: B vs A
blastp -query species_B.fasta -db species_A_db -outfmt 6 -evalue 1e-5 \
    -max_target_seqs 1 -out B_vs_A.tsv

# Find reciprocal best hits
awk 'NR==FNR {a[$1]=$2; next} $2 in a && a[$2]==$1' A_vs_B.tsv B_vs_A.tsv

Extract Hit Sequences

bash
# Get subject sequence by ID (requires -parse_seqids)
blastdbcmd -db my_db -entry "sequence_id" -out hit.fasta

# Get multiple sequences
blastdbcmd -db my_db -entry_batch ids.txt -out hits.fasta

# Get all sequences from database
blastdbcmd -db my_db -entry all -out all_seqs.fasta

Prebuilt Databases

Download from NCBI:

bash
# Download and extract (uses update_blastdb.pl)
update_blastdb.pl --decompress nt

# Or download manually from:
# https://ftp.ncbi.nlm.nih.gov/blast/db/

Common databases:

  • nt - All nucleotide sequences
  • nr - Non-redundant protein
  • refseq_rna - RefSeq RNA
  • swissprot - UniProt SwissProt

Common Errors

Error Cause Solution
BLAST Database error Database not found Check path, rebuild database
No hits found No matches or wrong DB type Verify database type matches query
Sequence too short Query below word size Lower word_size or use longer query
Out of memory Large database Reduce threads, use -num_threads 1

Local vs Remote BLAST

Aspect Local Remote
Speed Fast Can be slow
Databases Must download/create All NCBI DBs available
Throughput Unlimited Rate limited
Setup Requires installation Just Biopython
Updates Manual Automatic

Decision Tree

Running BLAST locally?
├── Have reference sequences?
│   └── makeblastdb to create database
├── Download NCBI database?
│   └── update_blastdb.pl or manual download
├── Need tabular output?
│   └── -outfmt 6 (or 7 with headers)
├── Filter low-complexity?
│   └── -dust yes (nucl) or -seg yes (prot)
├── Multiple queries?
│   └── Put all in one FASTA, use -num_threads
├── Need XML output?
│   └── -outfmt 5
└── Extract hit sequences?
    └── blastdbcmd -entry

Related Skills

  • blast-searches - Remote BLAST via NCBI (no installation needed)
  • sequence-io - Read/write FASTA files for queries
  • batch-downloads - Download sequences to build local databases

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