name: bio-blast-searches description: Run remote BLAST searches against NCBI servers using Biopython Bio.Blast.NCBIWWW. Use when identifying unknown sequences, finding homologs, picking the correct BLAST program (blastn/blastp/blastx/tblastn/tblastx/psiblast/megablast/dc-megablast), interpreting Karlin-Altschul E-values, avoiding the max_target_seqs trap (Shah 2019), choosing composition-based statistics, or limiting searches by organism. Covers RID lifecycle, database choice (nt/nr/refseq_select/swissprot), word-size and CBS taxonomy. origin: openai4s category: bioskills/database-access metadata: tool_type: python primary_tool: Bio.Blast.NCBIWWW third_party: name: GPTomics/bioSkills repository: https://github.com/GPTomics/bioSkills commit: d91ed3d563019e649dc854c56ccd62551359488a license: MIT
Reference examples tested with: BioPython 1.83+, NCBI BLAST+ 2.15+
Before using code patterns, verify installed versions match. If versions differ:
- Python: pip show biopython then help(Bio.Blast.NCBIWWW.qblast) to check signatures
- CLI: blastn -version then blastn -help
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
"Find similar sequences in NCBI's database" -> Submit a query to NCBI's remote BLAST servers; receive a Request ID (RID); poll for completion; parse the XML hit table. Best for one-off identification of a few sequences. For >50 sequences, switch to local-blast or DIAMOND/MMseqs2 in remote-homology.
The two most consequential decisions: which program (defines query+target molecule types and word-size defaults) and which database (defines the search space and therefore E-value baselines). The third most important: do NOT misuse max_target_seqs -- it is an early-termination heuristic, not a "give me the top N hits" filter (Shah et al. 2019).
NCBIWWW.qblast(program, db, sequence) + NCBIXML.read(handle) (BioPython)blastn -remote -db nt -query seq.fa -out hits.xml -outfmt 5 (BLAST+)from Bio.Blast import NCBIWWW, NCBIXML
from Bio import SeqIO
No API key needed for remote BLAST itself, but NCBI's general rate-limit ethic still applies -- one search at a time, polite waiting, no parallelism.
| Program | Query | Target | Word size default | Use case |
|---|---|---|---|---|
blastn |
DNA | DNA | 11 | General DNA similarity |
megablast |
DNA | DNA | 28 | High-identity DNA (>=95%) -- PCR primer hits, contamination |
dc-megablast |
DNA | DNA | 11 (discontiguous) | Cross-species mRNA (sensitive, gapped) |
blastp |
Protein | Protein | 3 (6 also valid) | General protein homology |
blastx |
DNA | Protein | 3 | Translated DNA query vs protein DB; ORF discovery |
tblastn |
Protein | DNA | 3 | Protein query vs translated DB; find unannotated CDS |
tblastx |
DNA | DNA | 3 (both translated) | Most expensive; deep cross-species coding similarity |
psiblast |
Protein | Protein | 3 | Iterative PSSM-based remote homology -- see remote-homology |
The misuse to avoid: using default blastn (word=11) for cross-species DNA where dc-megablast is the right tool. Or using megablast (word=28) for cross-species homology where it will miss every divergent hit. The most-misused BLAST parameter according to literature.
Database (db=) |
Content | Size (2026 approx) | Stable for reproducibility? |
|---|---|---|---|
nt |
Non-redundant nucleotide (all GenBank+EMBL+DDBJ) | ~250 GB | NO -- changes daily |
nr |
Non-redundant protein | ~300 GB | NO -- changes daily |
refseq_select |
One curated rep per species (RNA + protein) | small | YES -- versioned releases |
refseq_rna |
RefSeq mRNA | ~10 GB | YES |
refseq_protein |
RefSeq protein | small | YES |
swissprot |
UniProt Swiss-Prot (reviewed) | small | YES -- monthly releases |
pdb |
Protein structures | small | YES |
refseq_genomic |
RefSeq genomic | huge | YES |
env_nr / env_nt |
Environmental (metagenomic) | huge | YES |
For publication reproducibility, never search nt or nr without recording the snapshot date and ideally archiving a frozen copy. Default to refseq_select for any cross-species homology question; switch to nt/nr only when curated coverage is insufficient.
E-value = K * m * n * exp(-lambda * S), where m = effective query length, n = effective database size, lambda and K are scoring-matrix-dependent constants (Karlin & Altschul 1990 PNAS 87:2264).
| E-value | Bit-score (BLOSUM62, protein) | Interpretation |
|---|---|---|
| < 1e-50 | > 200 | Strong; almost certainly homologous |
| 1e-50 to 1e-10 | 100-200 | Significant; likely homolog |
| 1e-10 to 1e-3 | 50-100 | Marginal; check identity + coverage |
| 0.01 to 10 | 30-50 | Possible remote homolog; needs profile method |
| > 10 | < 30 | Random; not meaningful |
Key implication of E = K * m * n * exp(-lambda * S): the same alignment against a 100x larger database has a 100x larger E-value. Cross-database E-value comparison is meaningless. Bit-score is database-size normalized and is the right cross-database metric.
For protein remote homology where E is marginal (10^-3 to 10^-1), reach for profile methods: PSI-BLAST, jackhmmer, HHblits, or Foldseek -- see remote-homology skill.
Compositional bias inflates significance for low-complexity proteins. The CBS modes (Yu et al. 2006 Nucleic Acids Res 34:5966):
composition_based_statistics |
Mode | Use when |
|---|---|---|
| 0 | Off | Almost never |
| 1 | F&S 2002 score adjustment | Legacy compatibility |
| 2 | Yu&Altschul 2005 conditional score adjustment | Default since BLAST+ 2.2.17 -- correct for most cases |
| 3 | Universal statistics | Short queries (< 30 aa) where mode 2 over-corrects |
For protein queries under 30 aa, switch to CBS=3. For protein with known compositional bias (e.g. coiled-coil regions, signal peptides), CBS=2 is appropriate but consider hard-masking with SEG.
max_target_seqs trapThe misuse: max_target_seqs=10 is interpreted as "return the 10 most significant hits". It is not. The flag is an early termination parameter that affects which hits the search ever considers, not which it ultimately reports (Shah N, Nute MG, Warnow T, Pop M. (2019) Misunderstood parameter of NCBI BLAST impacts the correctness of bioinformatics workflows. Bioinformatics 35:1613-1614).
Consequences:
- Setting max_target_seqs=10 can return entirely different hits than max_target_seqs=500 then filtering to top 10 by E-value.
- The "top 10" by E-value as reported may not be the actual top 10.
Correct pattern: set hitlist_size (Bio.Blast parameter name) large (1000+), then post-filter to the top N by E-value or bit-score in Python.
| Search | Word size | Matrix (protein) | Gap (open, extend) |
|---|---|---|---|
| megablast (high identity DNA) | 28 | n/a | 0, 0 (linear) |
| blastn (sensitive DNA) | 11 | n/a | 5, 2 |
| blastp default | 3 | BLOSUM62 | 11, 1 |
| blastp distant | 2 | BLOSUM45 | 14, 2 |
| Short peptides (<30 aa) | 2 | PAM30 or BLOSUM45 | 9, 1 |
For very short query proteins (e.g. proteomics-identified peptides), BLOSUM45 + word=2 + PAM30 substitution matrix is more sensitive than the default. Use matrix='PAM30' for searches against swissprot.
| Phase | Server state | Client action |
|---|---|---|
| Submit | RID created, queued | NCBIWWW.qblast() returns handle |
| Running | Queue + compute | Poll status |
| Done | RID + results retained | Fetch XML |
| Expired | RID purged | 24-36h after completion |
NCBIWWW.qblast() handles polling internally with a fixed retry interval. For long-running searches (>5 min) or batches, submit and capture the RID, then poll independently to avoid blocking. The RID is visible at https://blast.ncbi.nlm.nih.gov/Blast.cgi?CMD=Get&RID=... for 24-36 hours.
Goal: Run BLASTN with explicit, paper-quality parameters.
Approach: Specify program, database (refseq_select for stability), word size, expect, and a large hitlist_size to dodge the max_target_seqs trap.
Reference (BioPython 1.83+):
from Bio.Blast import NCBIWWW, NCBIXML
handle = NCBIWWW.qblast(
program='blastn',
database='refseq_select_rna',
sequence=query_seq,
expect=1e-10,
word_size=11,
hitlist_size=500, # large; filter top-N downstream
format_type='XML',
)
record = NCBIXML.read(handle); handle.close()
top10 = sorted(record.alignments, key=lambda a: a.hsps[0].expect)[:10]
Goal: Find mammalian homologs of a query protein in Swiss-Prot.
Approach: entrez_query filters the BLAST search space pre-execution; faster and more meaningful E-values than post-filtering.
Reference (BioPython 1.83+):
handle = NCBIWWW.qblast(
program='blastp',
database='swissprot',
sequence=protein_seq,
entrez_query='Mammalia[Organism]',
expect=1e-5,
composition_based_statistics=2,
hitlist_size=200,
)
record = NCBIXML.read(handle); handle.close()
handle = NCBIWWW.qblast(
program='blastp',
database='swissprot',
sequence=peptide_seq, # < 30 aa
matrix_name='PAM30',
word_size=2,
expect=1000, # short queries need permissive cutoff
composition_based_statistics=3,
hitlist_size=100,
)
handle = NCBIWWW.qblast('blastn', 'refseq_select_rna', query)
with open('blast.xml', 'w') as f:
f.write(handle.read())
handle.close()
with open('blast.xml') as f:
record = NCBIXML.read(f)
Goal: Return structured top hits with biological metrics, not just E-values.
Approach: Walk alignments + first HSP; compute identity and query coverage as fractions; sort by bit-score (database-size invariant) not E-value.
Reference (BioPython 1.83+):
def top_hits(record, min_identity=0.5, min_coverage=0.7, top_n=10):
qlen = record.query_length
hits = []
for aln in record.alignments:
hsp = aln.hsps[0]
ident = hsp.identities / hsp.align_length
cov = hsp.align_length / qlen
if ident >= min_identity and cov >= min_coverage:
hits.append({
'accession': aln.accession,
'title': aln.title,
'evalue': hsp.expect,
'bits': hsp.bits,
'identity': ident,
'coverage': cov,
})
return sorted(hits, key=lambda h: -h['bits'])[:top_n]
import time
handle = NCBIWWW.qblast('tblastn', 'nr', query, hitlist_size=500, format_type='XML')
# Bio.Blast handles polling internally; for explicit control use the REST API directly
# or save and re-parse the RID URL
max_target_seqs misinterpretationhitlist_size=10 and assuming top 10 by E-value.hitlist_size=500+ and post-filter; cite Shah 2019.nt search against E from a swissprot search.megablast (word=28) on a cross-species DNA query.dc-megablast (discontiguous) or blastn with word=11.nt/nrrefseq_select for reproducibility, or record snapshot date + archive subset.local-blast / DIAMOND / MMseqs2.filter='S' (SEG).sequence as a raw string without >id\n.record.query is None.SeqRecord.| Error / symptom | Cause | Solution |
|---|---|---|
| Stuck > 5 min | Large query or busy queue | Submit RID, poll separately; or use local |
| URLError / timeout | Network or NCBI maintenance | Retry with backoff; status at status.ncbi.nlm.nih.gov |
| No hits | Wrong program / database type | Verify query and DB molecule types match |
| Empty XML | RID expired | Re-submit; RIDs purge after 24-36h |
| 1000s of low-complexity hits | CBS disabled or extreme bias | CBS=2; consider SEG filter |
| Cross-DB E mismatch | Comparing E across DBs | Use bit-score instead |