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Bio epitranscriptomics m6anet analysis

Skill FridrichMethod/awesome-skills/skills/bio-epitranscriptomics-m6anet-analysis

Detect m6A modifications from Oxford Nanopore direct RNA sequencing using m6Anet. Use when analyzing epitranscriptomic modifications from long-read RNA data without immunoprecipitation.From its SKILL.md

Install
npx -y skills add FridrichMethod/awesome-skills --skill bio-epitranscriptomics-m6anet-analysis

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SKILL.md

2.2 KB, 546 tokens by cl100k_base, as published. Nobody here has run it

<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <[email protected]> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA -->

m6Anet Analysis

Documentation: https://m6anet.readthedocs.io/

Data Preparation

# Basecall with Guppy (requires FAST5 files)
guppy_basecaller \
    -i fast5_dir \
    -s basecalled \
    --flowcell FLO-MIN106 \
    --kit SQK-RNA002

# Align to transcriptome
minimap2 -ax map-ont -uf transcriptome.fa reads.fastq > aligned.sam

Run m6Anet

from m6anet.utils import preprocess
from m6anet import run_inference

# Preprocess: extract features from FAST5
preprocess.run(
    fast5_dir='fast5_pass',
    out_dir='m6anet_data',
    reference='transcriptome.fa',
    n_processes=8
)

# Run m6A inference
run_inference.run(
    input_dir='m6anet_data',
    out_dir='m6anet_results',
    n_processes=4
)

CLI Workflow

# Preprocess
m6anet dataprep \
    --input_dir fast5_pass \
    --output_dir m6anet_data \
    --reference transcriptome.fa \
    --n_processes 8

# Inference
m6anet inference \
    --input_dir m6anet_data \
    --output_dir m6anet_results \
    --n_processes 4

Interpret Results

import pandas as pd

results = pd.read_csv('m6anet_results/data.site_proba.csv')

# Filter high-confidence m6A sites
# probability > 0.9: High confidence threshold
m6a_sites = results[results['probability_modified'] > 0.9]

Related Skills

  • long-read-sequencing - ONT data processing
  • m6a-peak-calling - MeRIP-seq alternative
  • modification-visualization - Plot m6A sites
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

What ships with it: 2 files

4.6 KB alongside SKILL.md, 1 of them executable

examples/

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