Systematic benchmarking of tools for CpG methylation detection from Nanopore sequencing

Abstract

DNA methylation plays a fundamental role in the control of gene expression and genome integrity. Although there are multiple tools that enable its detection from Nanopore sequencing, their accuracy remains largely unknown. Here, we present a systematic benchmarking of tools for the detection of CpG methylation from Nanopore sequencing using individual reads, control mixtures of methylated and unmethylated reads, and bisulfite sequencing. We found that tools showed a tradeoff between false positives and false negatives, and presented a high dispersion with respect to the expected methylation frequency values. We described various strategies to improve the accuracy of these tools and proposed a new method, METEORE (https://github.com/comprna/METEORE), based on the combination of the predictions from two or more tools that has improved accuracy over individual tools. Snakemake pipelines are provided for reproducibility and to enable the systematic application of our analyses to other datasets.