motif-search

Motif and Pattern Search

Hard rules

1. No fabricated citations. Every cited work must resolve to a verifiable
2. No claim without provenance. Every quantitative or factual claim
3. No silent failure. Every script invocation, API call, or tool use must declare its exit status and what to do on non-zero. A skill that silently swallows errors is a violation.

When to use

• Finding a known regulatory element in a sequence (TATA box, Kozak, poly-A).
• Scanning a promoter for a transcription factor binding site.
• Confirming an enzyme recognition site in a designed construct.
• Searching for a protein motif (PROSITE, Pfam) with a regex.

When NOT to use

• De novo motif discovery from ChIP-seq → use MEME / STREME.
• Genome-wide PWM scan → use MOODS, FIMO, or pyMOODS.
• Protein domain detection → use pyhmmer or InterProScan.

Prerequisites

• biopython>=1.83
• For advanced regex: regex package (supports fuzzy matching, IUPAC natively).
• For JASPAR motifs: pyjaspar (modern replacement for Biopython's JASPAR module).
• For genome-wide scans: MOODS (C++) or FIMO (MEME Suite).

Core workflow

1. Decide the motif type: literal, IUPAC, or PWM.
2. For literal/IUPAC: regex is fastest.
3. For PWM: convert to a log-odds matrix, scan with a sliding window.
4. Validate hits biologically (one perfect match in a 10 kb promoter is suspicious; a 7/8 match with a known co-factor is meaningful).

Code patterns

Literal motif (regex)

import re
from Bio import SeqIO

seq = str(next(SeqIO.parse("promoter.fasta", "fasta")).seq)
for m in re.finditer(r"TATAAA", seq):
    print(f"TATA box at {m.start()}")

IUPAC consensus

IUPAC codes are valid regex characters except a few that collide with regex syntax (*, ?, (, )). Use Biopython's IUPAC-to-regex helper:

from Bio.Data.IUPACData import ambiguous_dna_values

def iupac_to_regex(motif: str) -> str:
    """Convert IUPAC DNA to a regex character class."""
    return "".join(f"[{ambiguous_dna_values[c]}]" for c in motif.upper())

pat = re.compile(iupac_to_regex("RRRYYCC"))  # poly-A signal
for m in pat.finditer(seq):
    print(m.start(), m.group())

Reverse-strand search

Many regulatory motifs are on the antisense strand:

def find_on_both_strands(seq: str, motif_regex):
    rc = str(Seq(seq).reverse_complement())
    for strand, s in (("+", seq), ("-", rc)):
        for m in motif_regex.finditer(s):
            print(f"{strand}\t{m.start()}\t{m.group()}")

PROSITE-style protein motif

psp = re.compile(r"G.{1,2}GV[AGST]G[AGILV]KT")  # P-loop NTP-binding
for m in psp.finditer(str(protein.seq)):
    print(m.start(), m.group())

Fuzzy matching (sequencing errors)

regex package supports approximate matching with e<=N for up to N edits:

import regex
for m in regex.finditer(r"(TATAAA){e<=1}", seq):
    print(m.start(), m.group(), m.fuzzy_counts)

Position Weight Matrix (PWM) from a JASPAR-style count matrix

import numpy as np
from Bio import motifs

counts = motifs.CountsMatrix(
    [
        [10,  3,  1,  2],   # A
        [ 2,  8,  1,  3],   # C
        [ 1,  2,  9,  2],   # G
        [ 1,  2,  3,  7],   # T
    ],
    alphabet="ACGT",
)
pwm = counts.normalize(pseudocounts=0.5)
pssm = pwm.log_odds()    # log2 odds vs uniform

Scan a sequence with a PSSM

threshold = 5.0
for pos, score in pssm.search(seq, threshold=threshold, both=True):
    print(f"hit at {pos}, score={score:.2f}")

Load a JASPAR motif (modern, 2026)

import pyjaspar

# pyjaspar 2.x supports JASPAR 2024 releases
motif = pyjaspar.get_motif_by_id("MA0006.1")  # Arnt
pwm = motif.profile_matrix   # 4 x len

Reverse-complement-aware PWM scan (TF binding is double-stranded)

# Biopython's `search(both=True)` already does this
hits = list(pssm.search(seq, threshold=6.0, both=True))

Find all occurrences of restriction sites

from Bio.Restriction import EcoRI, BamHI, HindIII

sites = []
for enz in (EcoRI, BamHI, HindIII):
    for hit in enz.search(seq):
        sites.append((hit, enz))

Common pitfalls

• IUPAC in regex breaks silently. [ACGT] works, but R alone is just a literal R. Always use the Biopython IUPAC-to-regex helper.
• PWM scan without background correction gives wrong scores. Always use log-odds (PWM), not raw frequencies.
• JASPAR 2024 release restructured motif IDs — old MA0006.1 may be MA0006.2. pyjaspar handles aliases.
• TATA box at position 0 is a false positive. It's probably the start of a sequence header; offset by 50+ bp from a TSS.
• Single PWM hit ≠ functional binding site. Combine with chromatin accessibility (ATAC-seq), conservation (phastCons), and co-factor motifs for credible predictions.

Validation

• For known motifs, the hit count is in the expected ballpark (e.g., a TATA box should appear in ~30-50% of vertebrate Pol II promoters, not 100%).
• For a PSSM, scan a known positive sequence first to confirm the threshold.
• Forward- and reverse-strand hits should be roughly equal in a random sequence (motif symmetry test).

Open alternatives

References

• Biopython Bio.motifs: https://biopython.org/docs/latest/api/Bio.motifs.html
• JASPAR 2024: https://jaspar.genereg.net/
• MEME Suite: https://meme-suite.org/meme/
• pyjaspar: https://github.com/asntech/pyjaspar
• Companion: ors-bioinformatics-sequence-seq-objects, ors-bioinformatics-functional-motif-* skills.

Changelog

• 1.0.0 (2026-06-10): Initial adaptation by Pradyumna Jayaram from bio-motif-search (bioSkills-main/sequence-manipulation/motif-search).

Cross-references

Other skills in this category:

• batch-processing
• bowtie2-alignment
• bwa-alignment
• bwa-mem2-alignment
• codon-usage
• compressed-sequence-files
• fastq-quality-scores
• filter-sequences
• format-conversion
• hisat2-alignment
• paired-end-fastq
• pysam-genomics
• read-write-sequences
• reverse-complement
• sam-bam-basics
• samtools-bam-processing
• seq-objects
• sequence-properties
• sequence-slicing
• sequence-statistics
• star-alignment
• transcription-translation