H(O)TA: estimation of DNA methylation and hydroxylation levels and efficiencies from time course data

TL;DR

This paper introduces H(O)TA, a statistical method for estimating DNA methylation and hydroxylation levels from time course data, addressing the need for precise analysis of epigenetic modifications.

Contribution

The paper presents a novel statistical approach, H(O)TA, for accurately estimating methylation and hydroxylation levels from experimental time course data.

Findings

H(O)TA provides more accurate estimates than previous methods.

The method effectively captures dynamic changes in epigenetic modifications.

Application to real data demonstrates its practical utility.

Abstract

Methylation and hydroxylation of cytosines to form 5-methylcytosine (5mC) and 5-droxymethylcytosine (5hmC) belong to the most important epigenetic modifications and their vital role in the regulation of gene expression has been widely recognized. Recent experimental techniques allow to infer methylation and hydroxylation levels at CpG dinucleotides but require a sophisticated statistical analysis to achieve accurate estimates.