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pradyumnasagarpradyumnasagar/open-research-skills/skills/bioinformatics-sequence/reverse-complement/SKILL.md

reverse-complement

Skill8 starsChanged 5 months agoMITView on GitHub

Compute reverse complements, complements, and strand-aware operations on DNA/RNA — including IUPAC ambiguity support, batch processing, and the orientation trap.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 3 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

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  • Distinctive
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  1. Distinctive:

    No fabricated citations: Every cited work must resolve to a verifiable

    line 20
  2. Distinctive:

    No claim without provenance: Every quantitative or factual claim

    line 21
  3. Distinctive:

    No silent failure: Every script invocation, API call, or tool use must declare its exit status and what to do on non-zero.

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  4. Very specific:

    Strand annotation lost: If you take feature.extract(record.seq), the extracted Seq is a fresh sequence and the feature's strand info is …

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  5. Very specific:

    Assuming IUPAC ambiguity in hand-rolled code: Don't write your own s.translate(str.maketrans("ACGT", "TGCA")) — it breaks on N, R, Y, etc.

    line 167

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md
<!-- metadata: category: bioinformatics-sequence oversight: low version: 1.0.0 author: Pradyumna Jayaram tags: [bioinformatics-sequence, research] difficulty: intermediate -->

Reverse Complement and Strand Operations

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

  • Computing reverse complements of DNA/RNA for primer/probe design.
  • Translating minus-strand genes.
  • Converting a feature's coordinates from one strand to the other.
  • Building batch reverse-complement pipelines for FASTA/FASTQ.

When NOT to use

  • You actually want just the complement (preserving 5'→3' direction) — use .complement().
  • For very high-throughput reverse-complement (millions of reads), use seqkit or pyfastx.

Prerequisites

  • biopython>=1.83
  • For shell-scale: seqkit seq -r (reverse) and seqkit seq -p (reverse-complement)

Core workflow

  1. Decide: complement or reverse-complement?
  2. Use Bio.Seq's built-in methods (which handle IUPAC ambiguity correctly).
  3. For batch, stream records through a generator.
  4. Always log a sanity check (e.g., reverse-complement of reverse-complement is the original).

The orientation decision

You haveYou wantMethod
Coding strand (sense)mRNA sequence.transcribe()
Coding strand (sense)Protein.translate()
Template strand (antisense)Coding strand.reverse_complement() first, then .transcribe()
mRNAcDNA (T for U).back_transcribe()
Coding strand, want other strand's sequenceOther strand.reverse_complement()

Code patterns

Basic reverse complement

from Bio.Seq import Seq

s = Seq("ATGGCCATTGTAATGGGCCGCTGAAAGGGTGCCCGATAG")
s.reverse_complement()
# Seq('CTATCGGGCACCCTTTCAGCGGCCCATTACAATGGCCAT')

Complement (no reversal)

s = Seq("ATGC")
s.complement()   # Seq('TACG') — still 5'→3', just base-paired

IUPAC ambiguity is built-in

s = Seq("ATGNRYWSKM")
s.reverse_complement()
# Seq('MKRSWYNCAT') — all ambiguity codes are handled

IUPAC complement table:

ATCGRYSWKMBDHVN
TAGCYRSWMKVHDBN

RNA reverse complement

from Bio.Seq import Seq

rna = Seq("AUGCCAUUG")  # 5' → 3' mRNA
rna.reverse_complement_rna()  # 5' → 3' of the antisense strand

Or transcribe to DNA first:

dna = rna.back_transcribe()
dna.reverse_complement()

Reverse-complement every record in a FASTA

from Bio import SeqIO

def rc_records(in_path, out_path):
    with open(out_path, "w") as out:
        for rec in SeqIO.parse(in_path, "fasta"):
            rec.seq = rec.seq.reverse_complement()
            rec.id = f"{rec.id}_rc"
            rec.description = "reverse complement"
            SeqIO.write(rec, out, "fasta")

rc_records("input.fasta", "rc.fasta")

Batch with Polars/streaming

from Bio import SeqIO

with open("rc.fasta", "w") as out:
    for rec in SeqIO.parse("primers.fasta", "fasta"):
        rec.seq = rec.seq.reverse_complement()
        SeqIO.write(rec, out, "fasta")

Sanity check: revcomp of revcomp is identity

def assert_revcomp_identity(s):
    assert s == s.reverse_complement().reverse_complement()

Extract a feature and reverse-complement

from Bio import SeqIO

rec = next(SeqIO.parse("chr1.gb", "genbank"))
for feat in rec.features:
    if feat.type == "CDS" and feat.location.strand == -1:
        nt = feat.extract(rec.seq)
        cds = nt.reverse_complement()  # now on + strand
        print(cds.translate())

Reverse-complement a region of a chromosome

def rc_region(record, start, end):
    return record.seq[start:end].reverse_complement()

Common pitfalls

  • Complement instead of reverse-complement. The most common bug. If you're on the minus strand and you call .complement(), you'll be working on the wrong strand.
  • Lowercase sequences. .reverse_complement() works on lowercase; just remember the output is whatever case the input was.
  • RNA vs DNA. reverse_complement() is for DNA. For RNA, use reverse_complement_rna() or transcribe first.
  • Strand annotation lost. If you take feature.extract(record.seq), the extracted Seq is a fresh sequence and the feature's strand info is gone. Reverse-complement explicitly when you need to flip strand.
  • Assuming IUPAC ambiguity in hand-rolled code. Don't write your own s.translate(str.maketrans("ACGT", "TGCA")) — it breaks on N, R, Y, etc.

Validation

  • s.reverse_complement().reverse_complement() == s.
  • The first base of the reverse-complement is the complement of the last base of the input.
  • Length is preserved.
  • GC content is preserved (gc_fraction of input and rc are equal).

Open alternatives

NeedTool
FASTA reverse-complement at scaleseqkit seq -p -r in.fasta
FASTX reverse-complementseqtk seq -r in.fq
Reverse-complement in shell pipelinebioawk -c fastx '{print ">"$name"_rc\n"revcomp($seq)}' in.fasta
Reverse-complement on huge genomepyfastx (C-accelerated)

References

Changelog

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

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
  • motif-search
  • paired-end-fastq
  • pysam-genomics
  • read-write-sequences
  • sam-bam-basics
  • samtools-bam-processing
  • seq-objects
  • sequence-properties
  • sequence-slicing
  • sequence-statistics
  • star-alignment
  • transcription-translation

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