Nature CommunicationsBioinformaticsPeer-reviewed journal article
DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing
Peng NiiD, Fan NieiD, Zeyu ZhongiD, Jinrui Xu, Neng HuangiD, Jun Zhang, Haochen ZhaoiD, You Feng ZouiD, Yuanfeng HuangiD, Jinchen LiiD, Chuan‐Le XiaoiD, Feng LuoiD, Jianxin WangiD
Abstract
Long single-molecular sequencing, such as PacBio circular consensus sequencing (CCS) and nanopore sequencing, is advantageous in detecting DNA 5-methylcytosine (5mC) in CpGs, especially in repetitive genomic regions. However, existing methods for detecting 5mCpGs using PacBio CCS are less accurate and robust. Here, we present ccsmeth, a deep-learning method to detect DNA 5mCpGs using CCS reads. We sequence PCR-treated and M.SssI-treated DNA of one human sample using PacBio CCS for training ccsmeth. Using long ([≥]10Kb) CCS reads, ccsmeth achieves 0.90 accuracy and 0.97 AUC on 5mCpG detection at single-molecule resolution. At the genome-wide site level, ccsmeth achieves >0.90 correlations with bisulfite sequencing and nanopore sequencing using only 10x reads. Furthermore, we develop a Nextflow pipeline, ccsmethphase, to detect haplotype-aware methylation using CCS reads, and then sequence a Chinese family trio to validate it. ccsmeth and ccsmethphase can be robust and accurate tools for detecting DNA 5mCs using PacBio CCS.
- organism: human
- assay: long-read sequencing
- research focus: differential expression
- research focus: variant calling
- approach: deep learning
- Citations
- 113
- FWCI
- 10.04
- Field percentile
- top 1%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- High accuracy methylation identification tools on single molecular level for PacBio HiFi data
Ying Chen, Bo Wu, … Chuan‐Le Xiao·bioRxiv·Aug 14, 2024
- PAPET: a collection of performant algorithms to identify 5-methyl cytosine from PacBio SequelII data
Romain Groux, Ioannis Xénarios, Emanuel Schmid‐Siegert·bioRxiv·Mar 17, 2023
- Genome-wide Detection of Cytosine Methylations in Plant from Nanopore sequencing data using Deep Learning
Peng Ni, Neng Huang, … Jianxin Wang·Nature CommunicationsPeer-reviewed·Oct 13, 2021
- Assessing methylation detection for primary human tissue using Nanopore sequencing
Rylee M. Genner, Stuart Akeson, … Miten Jain·bioRxiv·Feb 29, 2024
- Rockfish: A Transformer-based Model for Accurate 5-Methylcytosine Prediction from Nanopore Sequencing
Dominik Stanojević, Zhe Li, … Mile Šikić·Nature CommunicationsPeer-reviewed·Jul 3, 2024
- DeepSignal: detecting DNA methylation state from Nanopore sequencing reads using deep-learning
Peng Ni, Neng Huang, … Jianxin Wang·BioinformaticsPeer-reviewed·Apr 11, 2019