Agent skill

bio-ribo-seq-riboseq-preprocessing

Preprocess ribosome profiling data including adapter trimming, size selection, rRNA removal, and alignment. Use when preparing Ribo-seq reads for downstream analysis of translation.

Stars 2,009
Forks 275

Install this agent skill to your Project

npx add-skill https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-ribo-seq-riboseq-preprocessing

SKILL.md

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: cutadaptbowtie2 (rRNA removal) → STAR (genome alignment)

Workflow Overview

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

bash
# 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.

bash
# Select ribosome footprint size range
# Typical: 28-32 nt (protected by ribosome)
cutadapt \
    -m 28 \
    -M 32 \
    -o size_selected.fastq.gz \
    trimmed.fastq.gz

rRNA Removal

Goal: Deplete ribosomal RNA reads that typically constitute the majority of a Ribo-seq library.

Approach: Align reads against rRNA reference databases using SortMeRNA or Bowtie2 and collect only unmapped (non-rRNA) reads.

bash
# Option 1: SortMeRNA (comprehensive)
sortmerna \
    --ref rRNA_databases/silva-bac-16s-id90.fasta \
    --ref rRNA_databases/silva-euk-18s-id95.fasta \
    --ref rRNA_databases/silva-euk-28s-id98.fasta \
    --reads size_selected.fastq.gz \
    --aligned rRNA_reads \
    --other non_rRNA_reads \
    --fastx \
    --threads 8

# Option 2: Bowtie2 to rRNA index
bowtie2 -x rRNA_index \
    -U size_selected.fastq.gz \
    --un non_rRNA.fastq.gz \
    -S /dev/null \
    -p 8

Alignment to Transcriptome

Goal: Map cleaned ribosome footprint reads to the genome or transcriptome for positional analysis.

Approach: Align with STAR (spliced) or Bowtie2 (transcriptome) using stringent filters for uniquely mapped reads with few mismatches.

bash
# STAR alignment (spliced)
STAR --runMode alignReads \
    --genomeDir STAR_index \
    --readFilesIn non_rRNA.fastq.gz \
    --readFilesCommand zcat \
    --outFilterMultimapNmax 1 \
    --outFilterMismatchNmax 2 \
    --alignIntronMax 1 \
    --outSAMtype BAM SortedByCoordinate \
    --outFileNamePrefix riboseq_

# Or bowtie2 to transcriptome
bowtie2 -x transcriptome_index \
    -U non_rRNA.fastq.gz \
    -S aligned.sam \
    --no-unal \
    -p 8

Quality Metrics

Goal: Assess preprocessing success by checking read length distribution and mapping rates.

Approach: Extract read lengths from the aligned BAM and run samtools flagstat to verify expected footprint sizes and mapping efficiency.

bash
# Check read length distribution
samtools view aligned.bam | \
    awk '{print length($10)}' | \
    sort | uniq -c | sort -k2n

# Expected: Peak at 28-30 nt

# Check mapping rate
samtools flagstat aligned.bam

Python Preprocessing

python
import pysam
import numpy as np
from collections import Counter

def get_length_distribution(bam_path):
    '''Get read length distribution from BAM'''
    lengths = Counter()
    with pysam.AlignmentFile(bam_path, 'rb') as bam:
        for read in bam:
            if not read.is_unmapped:
                lengths[read.query_length] += 1
    return lengths

def filter_by_length(bam_in, bam_out, min_len=28, max_len=32):
    '''Filter BAM by read length'''
    with pysam.AlignmentFile(bam_in, 'rb') as infile:
        with pysam.AlignmentFile(bam_out, 'wb', template=infile) as outfile:
            for read in infile:
                if min_len <= read.query_length <= max_len:
                    outfile.write(read)

Related Skills

  • ribosome-periodicity - Validate preprocessing quality
  • read-qc - General quality control
  • read-alignment - Alignment concepts

Expand your agent's capabilities with these related and highly-rated skills.

FreedomIntelligence/OpenClaw-Medical-Skills

vcf-annotator

Annotate VCF variants with VEP, ClinVar, gnomAD frequencies, and ancestry-aware context. Generates prioritised variant reports.

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

chemist-analyst

Analyzes events through chemistry lens using molecular structure, reaction mechanisms, thermodynamics, kinetics, and analytical techniques (spectroscopy, chromatography, mass spectrometry). Provides insights on chemical processes, material properties, reaction pathways, synthesis, and analytical methods. Use when: Chemical reactions, material analysis, synthesis planning, process optimization, environmental chemistry. Evaluates: Molecular structure, reaction mechanisms, yield, selectivity, safety, environmental impact.

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

bio-alignment-io

Read, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO. Supports Clustal, PHYLIP, Stockholm, FASTA, Nexus, and other alignment formats for phylogenetics and conservation analysis. Use when reading, writing, or converting alignment file formats.

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

sleep-analyzer

分析睡眠数据、识别睡眠模式、评估睡眠质量,并提供个性化睡眠改善建议。支持与其他健康数据的关联分析。

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

metabolomics-workbench-database

Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

bio-hi-c-analysis-matrix-operations

Balance, normalize, and transform Hi-C contact matrices using cooler and cooltools. Apply iterative correction (ICE), compute expected values, and generate observed/expected matrices. Use when normalizing or transforming Hi-C matrices.

2,009 275
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results