Systematic benchmarking of tools for CpG methylation detection from Nanopore sequencing

Yuen, ZW-S; Srivastava, A; Daniel, R; McNevin, D; Jack, C; Eyras, E

Systematic benchmarking of tools for CpG methylation detection from Nanopore sequencing

Yuen, ZW-S Srivastava, A Daniel, R McNevin, D

Jack, C Eyras, E

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Publication Type:: Working Paper
Citation:: bioRxiv, 2020
Issue Date:: 2020-10-15

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Field	Value	Language
dc.contributor.author	Yuen, ZW-S
dc.contributor.author	Srivastava, A
dc.contributor.author	Daniel, R
dc.contributor.author	McNevin, D https://orcid.org/0000-0003-1665-3367
dc.contributor.author	Jack, C
dc.contributor.author	Eyras, E
dc.date.accessioned	2022-01-31T22:23:09Z
dc.date.available	2022-01-31T22:23:09Z
dc.date.issued	2020-10-15
dc.identifier.citation	bioRxiv, 2020
dc.identifier.uri	http://hdl.handle.net/10453/153995
dc.description.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 have a tradeoff between false positives and false negatives and present a high dispersion with respect to the expected methylation frequency values. We described various strategies to improve the accuracy of these tools, including a new consensus approach, METEORE ( https://github.com/comprna/METEORE ), based on the combination of the predictions from two or more tools that shows improved accuracy over individual tools. Snakemake pipelines are also provided for reproducibility and to enable the systematic application of our analyses to other datasets.
dc.language	en
dc.relation.ispartof	bioRxiv
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Systematic benchmarking of tools for CpG methylation detection from Nanopore sequencing
dc.type	Working Paper
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Strength - CFS - Centre for Forensic Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	open_access	*
dc.date.updated	2022-01-31T22:23:08Z

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 have a tradeoff between false positives and false negatives and present a high dispersion with respect to the expected methylation frequency values. We described various strategies to improve the accuracy of these tools, including a new consensus approach, METEORE ( https://github.com/comprna/METEORE ), based on the combination of the predictions from two or more tools that shows improved accuracy over individual tools. Snakemake pipelines are also provided for reproducibility and to enable the systematic application of our analyses to other datasets.

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http://hdl.handle.net/10453/153995