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SegPore

SegPore is a software to segment the raw signal of nanopore direct RNA sequencing and estimate the RNA modifications.

Install / Use

/learn @guangzhaocs/SegPore
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

SegPore: Raw Signal Segmentation for Estimating RNA Modification from Nanopore Direct RNA Sequencing Data

Read the manuscript Release License GitHub Stars

<div align="center"> <img src=docs/media/SegPore_anim.gif width=80% /> <img src=docs/media/github_pic.png width=95% /> </div>

SegPore Workflow

More details on SegPore tutorials.

Environment setup

git clone https://github.com/guangzhaocs/SegPore.git
cd SegPore
conda env create -f environment.yml
conda activate segpore_env
pip3 install git+https://github.com/EGA-archive/ont2cram
# install Guppy

Download demo data

Here we use the WT demo data of xPore.

cd SegPore
wget https://zenodo.org/record/5162402/files/demo.tar.gz
tar -xvf demo.tar.gz
cd scripts
sh 0_data_proc.sh

Step 1: Basecalling, mapping and preprocessing

sh 1_basecalling.sh
sh 1_nanopolish.sh

Step 2: Hierarchical hidden Markov model (HHMM) for signal segmentation

2.1 Firstly, prepare the input of HHMM.

sh 2_hhmm_prepare.sh

2.2 Next, run HHMM on CUDA:

sh 2_hhmm_GPU.sh

2.3 Finally, generate the final output:

sh 2_hhmm_post_proc.sh

Step 3: Alignment of signal segments with reference sequence

sh 3_alignment.sh

Step 4: GMM to update 5mer parameter table

Fix the mean of the first component of GMM.

sh 4_gmm.sh

Use the results of GMM to update the 5mer parameter table and iteratively run Step 3 and Step 4.

Cite SegPore

Guangzhao Cheng, Aki Vehtari, Lu Cheng (2026) Raw signal segmentation for estimating RNA modification from Nanopore direct RNA sequencing data eLife 14:RP104618

@article {10.7554/eLife.104618,
article_type = {journal},
title = {Raw signal segmentation for estimating RNA modification from Nanopore direct RNA sequencing data},
author = {Cheng, Guangzhao and Vehtari, Aki and Cheng, Lu},
editor = {Altemose, Nicolas and Moses, Alan M},
volume = 14,
year = 2026,
month = {mar},
pub_date = {2026-03-02},
pages = {RP104618},
citation = {eLife 2026;14:RP104618},
doi = {10.7554/eLife.104618},
url = {https://doi.org/10.7554/eLife.104618},
keywords = {Nanopore, RNA modification, raw signal, alignment, segmentation},
journal = {eLife},
issn = {2050-084X},
publisher = {eLife Sciences Publications, Ltd},
}

Reference

  1. Pratanwanich, P.N., Yao, F., Chen, Y. et al. Identification of differential RNA modifications from nanopore direct RNA sequencing with xPore. Nat Biotechnol 39, 1394–1402 (2021). https://doi.org/10.1038/s41587-021-00949-w
  2. Zhong, ZD., Xie, YY., Chen, HX. et al. Systematic comparison of tools used for m6A mapping from nanopore direct RNA sequencing. Nat Commun 14, 1906 (2023). https://doi.org/10.1038/s41467-023-37596-5

Related Skills

View on GitHub
GitHub Stars13
CategoryDevelopment
Updated26d ago
Forks2

Languages

Python

Security Score

95/100

Audited on Mar 3, 2026

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