Version Compatibility

Reference examples tested with: Bowtie2 2.5.3+, STAR 2.7.11+, cutadapt 4.4+, numpy 1.26+, pysam 0.22+, samtools 1.19+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Ribo-seq Preprocessing

"Preprocess my ribosome profiling data" → Trim adapters, size-select ribosome-protected fragments (26-34 nt), remove rRNA contamination, and align to the transcriptome for translation analysis.

• CLI: cutadapt → bowtie2 (rRNA removal) → STAR (genome alignment)

Workflow Overview

Raw Ribo-seq FASTQ
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    v
Adapter trimming (cutadapt)
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    v
Size selection (25-35 nt typical)
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    v
rRNA removal (SortMeRNA/bowtie2)
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    v
Alignment to transcriptome
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    v
Quality filtered BAM

Adapter Trimming

Goal: Remove 3' adapter sequences from ribosome footprint reads to recover the true insert.

Approach: Run cutadapt with the known adapter sequence and length filters to discard fragments outside the expected footprint range.

# Trim 3' adapter
cutadapt \
    -a CTGTAGGCACCATCAAT \
    -m 20 \
    -M 40 \
    -o trimmed.fastq.gz \
    input.fastq.gz

Size Selection

Goal: Retain only reads corresponding to ribosome-protected fragments (typically 28-32 nt).

Approach: Apply minimum and maximum length filters with cutadapt to select the footprint size range.