sequence-slicing

name	sequence-slicing
description	Slice, subset, and extract regions from sequences and SeqRecords — including feature extraction, fuzzy ends, and the location algebra behind GenBank features.
license	MIT

Sequence Slicing and Subsetting

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

• Extracting a gene/CDS/exon from a chromosome sequence.
• Slicing reads or contigs by position.
• Computing intersection of two locations (e.g., variant overlaps a gene).
• Fuzzy-end handling (next-generation sequencing produces 5'..<200).

When NOT to use

• Production genomic region queries → use pyranges or pysam with a BED file.
• Whole-genome windowed stats → use bedtools or deeptools.

Prerequisites

• biopython>=1.83
• For 1-based / 0-based conversion discipline, see below.

Core workflow

1. Decide the coordinate system. Biopython FeatureLocation is 0-based, end-exclusive, matching BED and Python. GenBank flat files are 1-based, end-inclusive.
2. For a GenBank feature, use feature.extract(record.seq) — Biopython handles strand for you.
3. For a manual region, slice with Python: record.seq[start:end].
4. For compound locations (e.g., joins across exons), extract walks the parts.

Coordinate systems

Tool / format	0/1-based	Start	End
Biopython FeatureLocation	0-based	inclusive	exclusive
Python seq[a:b]	0-based	inclusive	exclusive
GenBank flat file	1-based	inclusive	inclusive
BED	0-based	inclusive	exclusive
GFF3	1-based	inclusive	inclusive
VCF	1-based	inclusive	(length-1)

The single most common bug in bioinformatics code is a 1-based / 0-based off-by-one. Pick a convention and stick to it.

Code patterns

Slice a record

from Bio import SeqIO

rec = next(SeqIO.parse("chr1.fasta", "fasta"))
seq = rec.seq[1000:2000]   # 1000 bp window, 0-based

Extract a feature (Biopython handles strand)

for feat in rec.features:
    if feat.type == "CDS":
        nt = feat.extract(rec.seq)  # always in 5'→3' of the feature's strand
        protein = nt.translate()
        print(feat.qualifiers.get("gene", ["?"])[0], protein)

Manual CDS extraction (start, end, strand)

from Bio.Seq import Seq

def extract_region(seq, start, end, strand):
    sub = seq[start:end]
    return sub.reverse_complement() if strand == -1 else sub

extract_region(rec.seq, 1000, 1500, strand=-1)

Compound location (multi-exon)

from Bio.SeqFeature import CompoundLocation

# join(100..200, 300..400)
loc = CompoundLocation([
    FeatureLocation(100, 200, strand=1),
    FeatureLocation(300, 400, strand=1),
])
nt = loc.extract(rec.seq)  # concatenates both parts

Fuzzy-end locations (next-gen sequencing)

GenBank uses > and < for unknown bounds. Biopython supports them with BeforePosition / AfterPosition:

from Bio.SeqFeature import FeatureLocation, BeforePosition

# >100..200  (start unknown, somewhere before 100)
loc = FeatureLocation(BeforePosition(100), 200)

Find which features overlap a window

def overlapping(feat, start, end):
    return not (feat.location.end <= start or feat.location.start >= end)

hits = [f for f in rec.features if overlapping(f, 1000, 2000)]

Construct a SimpleLocation and check strand

from Bio.SeqFeature import SimpleLocation

loc = SimpleLocation(100, 200, strand=1)
print(loc.start, loc.end, loc.strand)   # 100 200 1

Convert 1-based GenBank coords to 0-based Python

def gb_to_python(start_gb, end_gb):
    # GenBank: 1-based inclusive; Python: 0-based exclusive
    return start_gb - 1, end_gb

Slice a FASTQ read

from Bio import SeqIO

rec = next(SeqIO.parse("reads.fastq", "fastq"))
subseq = rec.seq[10:50]   # a 40 bp window

Take a sub-record (preserves ID and metadata)

sub = rec[1000:2000]
print(sub.id, sub.description)

Common pitfalls

• 1-based GenBank vs 0-based Python. Always convert explicitly.
• End-exclusive Python vs end-inclusive GenBank. seq[99:199] is 100 bp, but GenBank would write it as 100..199.
• Forgetting strand on manual extraction. seq[start:end] always returns the + strand. To get the - strand, .reverse_complement().
• Fuzzy bounds silently coerced. BeforePosition and AfterPosition are real; don't pretend they're integers.
• Slicing a Seq vs slicing a SeqRecord. Slicing a record returns a new SeqRecord (preserves ID/description). Slicing a Seq returns a Seq.

Validation

• len(rec.seq[1000:2000]) == 1000.
• For a CDS feature, the extracted length should be a multiple of 3.
• Round-trip: loc.extract(rec.seq) length equals the sum of the location parts.

Open alternatives

Need	Tool
Production genomic windows	pyranges, polars-bio
BED-style intersections	bedtools intersect
Tabix region queries	pysam.TabixFile.fetch(...)
Variant overlap with genes	pyensembl, gffutils

References

• Biopython SeqFeature: https://biopython.org/docs/latest/api/Bio.SeqFeature.html
• Location algebra: https://biopython.org/docs/latest/Tutorial.html#sec:locations
• Companion: ors-bioinformatics-sequence-seq-objects, ors-bioinformatics-omics-genome-intervals-* skills.

Changelog

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

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
• reverse-complement
• sam-bam-basics
• samtools-bam-processing
• seq-objects
• sequence-properties
• sequence-statistics
• star-alignment
• transcription-translation