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bio-ribo-seq-ribosome-periodicity

Maintainer FreedomIntelligence · Last updated April 1, 2026

Validate Ribo-seq data quality by checking 3-nucleotide periodicity and calculating P-site offsets. Use when assessing library quality or determining read offsets for downstream analysis.

OpenClawNanoClawAnalysisReproductionbio-ribo-seq-ribosome-periodicity🧬 bioinformatics (gptomics bio-* suite)bioinformatics — differential expression & transcriptomicsvalidate

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-ribo-seq-ribosome-periodicity

Maintainer
FreedomIntelligence
License
MIT
Last updated
April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

  • Python: plastid for P-site offset calculation and metagene analysis.
  • Check if my Ribo-seq data shows triplet periodicity" → Validate Ribo-seq library quality by verifying 3-nucleotide translocation patterns and calculating P-site offsets from metagene profiles. Python: plastid for P-site offset calculation and metagene analysis.
  • alignments = BAMGenomeArray('riboseq.bam', mapping=FivePrimeMapFactory()).

Source Doc

Excerpt From SKILL.md

3-Nucleotide Periodicity

Goal: Verify that Ribo-seq reads exhibit the expected 3-nucleotide translocation pattern characteristic of active translation.

Approach: Load P-site mapped reads and compute metagene profiles around start codons to check for triplet periodicity.

Ribosomes move 3 nucleotides per codon. Good Ribo-seq data shows strong periodicity:

from plastid import BAMGenomeArray, FivePrimeMapFactory, GenomicSegment
import numpy as np
import matplotlib.pyplot as plt

## Calculate P-site Offset

**Goal:** Determine the optimal P-site offset from the 5' end of ribosome footprints for accurate codon-level positioning.

**Approach:** Run metagene analysis around annotated start codons and identify the offset that aligns the signal peak with the AUG position.

```python
from plastid import metagene_analysis

## Typically 12-15 nt from 5' end for 28-30 nt reads

def determine_psite_offset(bam_path, annotation_file):
    '''Determine optimal P-site offset from metagene analysis'''
    from plastid import GTF2_TranscriptAssembler, BAMGenomeArray

    # Load annotations
    transcripts = list(GTF2_TranscriptAssembler(annotation_file))

    # Load reads
    alignments = BAMGenomeArray(bam_path, mapping=FivePrimeMapFactory())

    # Metagene around start codons
    # Peak should align with start codon position
    metagene_data = metagene_analysis(
        transcripts,
        alignments,
        upstream=50,
        downstream=100
    )

    return metagene_data

Use cases

  • Use when assessing library quality or determining read offsets for downstream analysis.

Not for

  • Do not rely on this catalog entry alone for installation or maintenance details.

Upstream Related Skills

  • riboseq-preprocessing - Generate aligned BAM
  • orf-detection - Uses P-site offsets
  • translation-efficiency - Requires proper positioning

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