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Updated: Oct 11, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

The SEQC2 epigenomics quality control (EpiQC) study.

Jonathan Foox^1,2, Jessica Nordlund^3,4, Claudia Lalancette⁵

¹Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York, USA.

|December 7, 2021

Summary

This summary is machine-generated.

This study benchmarks multiple DNA methylation sequencing methods, finding high concordance but also platform-specific differences. The results offer guidance for epigenetics research and best practices for experimental design using reference materials.

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Last Updated: Oct 11, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

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Published on: August 3, 2018

A Semiautomated ChIP-Seq Procedure for Large-scale Epigenetic Studies

A Semiautomated ChIP-Seq Procedure for Large-scale Epigenetic Studies

Published on: August 13, 2020

Chromatin Immunoprecipitation of Murine Brown Adipose Tissue

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Published on: November 21, 2018

Area of Science:

Epigenetics
Genomics
Molecular Biology

Background:

DNA methylation, including 5-methylcytosine (5mC), is crucial for development, cell lineage, and disease stratification.
Diverse interrogation methods necessitate harmonization and benchmarking for reliable genome-wide methylome sequencing.
The FDA's Epigenomics Quality Control Group provides a cross-validated resource for epigenetics research.

Purpose of the Study:

To conduct a multi-platform assessment of DNA methylation analysis techniques.
To establish harmonized materials and methods for epigenetics research.
To provide a benchmark for improving genome-wide methylome sequencing applications.

Main Methods:

Evaluation of multiple whole-genome bisulfite sequencing (WGBS) protocols, oxidative bisulfite sequencing, enzymatic deamination, targeted methylation sequencing, nanopore sequencing, and methylation arrays.
Rigorous quality assessment, cross-validation against Illumina EPIC microarrays, and testing of various analysis algorithms.
Utilizing seven human cell lines as publicly available reference materials.

Main Results:

High overall concordance was observed between different DNA methylation assays.
Differences were noted in read mapping efficiency, CpG capture, coverage, and platform performance.
Variable performance was found across 26 microarray normalization algorithms.

Conclusions:

The presented data guide the use of DNA reference materials in epigenomics.
Best practices for experimental design in future epigenetics studies are provided.
The findings establish a baseline for advancing epigenomics research using standardized reference materials.