SegPore: Raw Signal Segmentation for Estimating RNA Modifications and Structures from Nanopore Direct RNA Sequencing Data

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.

Citation

Cheng, Guangzhao, Aki Vehtari, and Lu Cheng. "Raw signal segmentation for estimating RNA modifications and structures from Nanopore direct RNA sequencing data." bioRxiv (2024): 2024-01. https://doi.org/10.1101/2024.01.11.575207

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