bio-blast-searches

---

name: bio-blast-searches description: Run remote BLAST searches against NCBI databases using Biopython Bio.Blast. Use when identifying unknown sequences, finding homologs, or searching for sequence similarity against NCBI's nr/nt databases. tool_type: python primary_tool: Bio.Blast.NCBIWWW measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

• read_file
• run_shell_command

---

BLAST Searches

Run BLAST searches against NCBI databases using Biopython's Bio.Blast module.

Required Import

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

BLAST Programs

Program	Query	Database	Use Case
blastn	Nucleotide	Nucleotide	DNA/RNA sequence similarity
blastp	Protein	Protein	Protein sequence similarity
blastx	Nucleotide	Protein	Find protein hits for DNA query
tblastn	Protein	Nucleotide	Find DNA encoding protein-like
tblastx	Nucleotide	Nucleotide	Translated vs translated

Core Function

NCBIWWW.qblast()

Submit a BLAST query to NCBI servers.

from Bio.Blast import NCBIWWW

# Simple BLASTN search
result_handle = NCBIWWW.qblast('blastn', 'nt', sequence)

Key Parameters:

Parameter	Description	Example
program	BLAST program	'blastn', 'blastp'
database	Target database	'nr', 'nt', 'refseq_rna'
sequence	Query sequence	String or SeqRecord
entrez_query	Limit by Entrez query	'Homo sapiens[organism]'
hitlist_size	Max hits to return	50
expect	E-value threshold	0.001
word_size	Word size	11 for blastn
gapcosts	Gap penalties	'5 2' (open, extend)
format_type	Output format	'XML' (default), 'Text'

Common Databases

Nucleotide:

Database	Description
nt	All GenBank + EMBL + DDBJ
refseq_rna	RefSeq RNA sequences
refseq_genomic	RefSeq genomic sequences

Protein:

Database	Description
nr	Non-redundant protein
refseq_protein	RefSeq proteins
swissprot	SwissProt (curated)
pdb	Protein structures

Parsing Results

NCBIXML Parser

from Bio.Blast import NCBIWWW, NCBIXML

# Run BLAST
result_handle = NCBIWWW.qblast('blastn', 'nt', sequence)

# Parse XML results
blast_record = NCBIXML.read(result_handle)
result_handle.close()

# Iterate hits
for alignment in blast_record.alignments:
    print(f"Hit: {alignment.title}")
    for hsp in alignment.hsps:
        print(f"  E-value: {hsp.expect}")
        print(f"  Score: {hsp.score}")
        print(f"  Identity: {hsp.identities}/{hsp.align_length}")

Alignment/HSP Attributes

# Alignment (hit) attributes
alignment.title          # Hit description
alignment.accession      # Accession number
alignment.length         # Subject sequence length
alignment.hsps           # List of HSPs

# HSP (High-scoring Segment Pair) attributes
hsp.score               # Raw score
hsp.bits                # Bit score
hsp.expect              # E-value
hsp.identities          # Number of identical positions
hsp.positives           # Number of positive-scoring positions
hsp.gaps                # Number of gaps
hsp.align_length        # Alignment length
hsp.query               # Aligned query sequence
hsp.match               # Match line (| for identity)
hsp.sbjct               # Aligned subject sequence
hsp.query_start         # Query start position
hsp.query_end           # Query end position
hsp.sbjct_start         # Subject start position
hsp.sbjct_end           # Subject end position
hsp.strand              # Strand (blastn)
hsp.frame               # Reading frame (blastx/tblastn)

Code Patterns

Basic BLASTN

from Bio.Blast import NCBIWWW, NCBIXML

sequence = '''ATGAAAGCAATTTTCGTACTGAAAGGTTGGTGGCGCACTTCCTGA'''

print("Running BLASTN (this may take a minute)...")
result_handle = NCBIWWW.qblast('blastn', 'nt', sequence)

blast_record = NCBIXML.read(result_handle)
result_handle.close()

print(f"\nFound {len(blast_record.alignments)} hits")
for alignment in blast_record.alignments[:5]:
    hsp = alignment.hsps[0]
    print(f"\n{alignment.title[:70]}...")
    print(f"  E-value: {hsp.expect:.2e}")
    print(f"  Identity: {hsp.identities}/{hsp.align_length} ({100*hsp.identities/hsp.align_length:.1f}%)")

BLASTP with Organism Filter

from Bio.Blast import NCBIWWW, NCBIXML

protein_seq = '''MVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSH'''

result_handle = NCBIWWW.qblast(
    'blastp',
    'nr',
    protein_seq,
    entrez_query='Mammalia[organism]',
    hitlist_size=20,
    expect=0.001
)

blast_record = NCBIXML.read(result_handle)
result_handle.close()

for alignment in blast_record.alignments[:10]:
    hsp = alignment.hsps[0]
    print(f"{alignment.accession}: E={hsp.expect:.2e} - {alignment.title[:50]}...")

BLAST from FASTA File

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

record = SeqIO.read('query.fasta', 'fasta')

result_handle = NCBIWWW.qblast('blastn', 'nt', record.seq)
blast_record = NCBIXML.read(result_handle)
result_handle.close()

for alignment in blast_record.alignments[:5]:
    print(f"{alignment.accession}: {alignment.title[:60]}...")

Save Results to File

from Bio.Blast import NCBIWWW

result_handle = NCBIWWW.qblast('blastn', 'nt', sequence)

# Save XML for later parsing
with open('blast_results.xml', 'w') as out:
    out.write(result_handle.read())
result_handle.close()

# Parse saved file
from Bio.Blast import NCBIXML
with open('blast_results.xml') as f:
    blast_record = NCBIXML.read(f)

Extract Top Hits

def get_top_hits(sequence, program='blastn', database='nt', num_hits=10, evalue=0.01):
    result_handle = NCBIWWW.qblast(
        program, database, sequence,
        hitlist_size=num_hits,
        expect=evalue
    )
    blast_record = NCBIXML.read(result_handle)
    result_handle.close()

    hits = []
    for alignment in blast_record.alignments:
        hsp = alignment.hsps[0]
        hits.append({
            'accession': alignment.accession,
            'title': alignment.title,
            'evalue': hsp.expect,
            'identity': hsp.identities / hsp.align_length,
            'coverage': hsp.align_length / blast_record.query_length
        })
    return hits

hits = get_top_hits(my_sequence, num_hits=5)
for hit in hits:
    print(f"{hit['accession']}: {hit['identity']:.1%} identity, E={hit['evalue']:.2e}")

BLASTX (DNA to Protein)

from Bio.Blast import NCBIWWW, NCBIXML

dna_sequence = '''ATGAAAGCAATTTTCGTACTGAAAGGTTGGTGGCGCACTTCCTGA'''

result_handle = NCBIWWW.qblast('blastx', 'nr', dna_sequence)
blast_record = NCBIXML.read(result_handle)
result_handle.close()

for alignment in blast_record.alignments[:5]:
    hsp = alignment.hsps[0]
    print(f"{alignment.accession}: frame {hsp.frame}, E={hsp.expect:.2e}")
    print(f"  {alignment.title[:60]}...")

Multiple Sequences

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

def blast_multiple(fasta_file, program='blastn', database='nt'):
    results = {}
    for record in SeqIO.parse(fasta_file, 'fasta'):
        print(f"BLASTing {record.id}...")

        result_handle = NCBIWWW.qblast(program, database, str(record.seq), hitlist_size=5)
        blast_record = NCBIXML.read(result_handle)
        result_handle.close()

        results[record.id] = blast_record
        time.sleep(5)  # Be nice to NCBI servers

    return results

Filter by Identity/Coverage

def filter_blast_hits(blast_record, min_identity=0.9, min_coverage=0.8):
    query_length = blast_record.query_length
    filtered = []

    for alignment in blast_record.alignments:
        for hsp in alignment.hsps:
            identity = hsp.identities / hsp.align_length
            coverage = hsp.align_length / query_length

            if identity >= min_identity and coverage >= min_coverage:
                filtered.append({
                    'accession': alignment.accession,
                    'title': alignment.title,
                    'identity': identity,
                    'coverage': coverage,
                    'evalue': hsp.expect
                })

    return filtered

Common Errors

Error	Cause	Solution
Timeout	NCBI servers busy	Retry later, use smaller query
No hits	Wrong database or program	Check program/database match
Empty results	E-value too stringent	Increase expect parameter
URLError	Network issue	Check connection, retry

Timing Notes

• Remote BLAST can take 30 seconds to several minutes
• Longer queries take longer
• Peak times (US business hours) may be slower
• For many queries, consider local BLAST

Decision Tree

Need to BLAST a sequence?
├── DNA query?
│   ├── Against DNA database? → blastn
│   └── Against protein database? → blastx
├── Protein query?
│   ├── Against protein database? → blastp
│   └── Against DNA database? → tblastn
├── Want to limit organisms?
│   └── Use entrez_query parameter
├── Need many searches?
│   └── Consider local-blast skill
└── Need results fast?
    └── Use local-blast skill

Related Skills

• local-blast - Run BLAST locally for faster, unlimited searches
• entrez-fetch - Fetch full records for BLAST hits
• sequence-io - Read query sequences from files