Reproducibility-optimized detection of differential DNA methylation

Epigenomics. 2020 May;12(9):747-755. doi: 10.2217/epi-2019-0289. Epub 2020 Jun 4.

Abstract

Aim: DNA methylation is a key epigenetic mechanism regulating gene expression. Identifying differentially methylated regions is integral to DNA methylation analysis and there is a need for robust tools reliably detecting regions with significant differences in their methylation status. Materials & methods: We present here a reproducibility-optimized test statistic (ROTS) for detection of differential DNA methylation from high-throughput sequencing or array-based data. Results: Using both simulated and real data, we demonstrate the ability of ROTS to identify differential methylation between sample groups. Conclusion: Compared with state-of-the-art methods, ROTS shows competitive sensitivity and specificity in detecting consistently differentially methylated regions.

Keywords: DNA methylation; ROTS; differential methylation; reduced representation bisulfite sequencing; reproducibility.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Carcinoma, Renal Cell / genetics
  • Carcinoma, Renal Cell / metabolism
  • DNA Methylation*
  • Data Interpretation, Statistical
  • Embryonic Stem Cells / metabolism
  • High-Throughput Nucleotide Sequencing / methods
  • Humans
  • Kidney Neoplasms / genetics
  • Kidney Neoplasms / metabolism
  • Oligonucleotide Array Sequence Analysis / methods
  • Reproducibility of Results
  • Sequence Analysis, DNA / methods*