Quantitative detection of DNA methylation from nanopore sequencing data without raw signals
Zhixing Feng, Chenxi Zhang, Shuo Jin, Jiale Niu, Huijuan Feng

TL;DR
A new method called NanoFreeLunch detects DNA methylation from nanopore sequencing data without needing raw signals, enabling large-scale epigenome studies.
Contribution
NanoFreeLunch is a novel method that detects DNA methylation using base quality values and error patterns instead of raw nanopore signals.
Findings
NanoFreeLunch shows strong correlation (0.87-0.94) with benchmark methylation levels at individual genomic loci.
Average methylation levels estimated by NanoFreeLunch correlate highly (0.97-0.99) with existing methods.
Abstract
Nanopore sequencing has revolutionized the field of epigenomics by enabling direct detection of DNA methylation without additional sample preprocessing such as bisulfite treatment. It is theoretically possible to reutilize any nanopore sequencing data to construct epigenomes. However, reutilizing the data in practice is challenging with existing methods because they rely on raw signals from nanopore sequencing, which are absent in more than 98% of public nanopore sequencing data. Moreover, storing raw signals for large-scale sequencing projects is impractical due to their enormous file sizes. To overcome these limitations, we propose a novel method, NanoFreeLunch, which can quantitatively detect DNA methylation without the need for raw signals by modeling base quality values and sequencing error patterns. Our results demonstrated a strong correlation between the DNA methylation levels…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsGenomics and Phylogenetic Studies · Nanopore and Nanochannel Transport Studies · Epigenetics and DNA Methylation
