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bioRxivGenomicsPreprint

Calling differential DNA methylation at cell-type resolution: addressing misconceptions and best practices

Elior RahmaniiD, Brandon JewiD, Regev SchweigeriD, Brooke L. RheadiD, Lindsey A. CriswelliD, Lisa F. BarcellosiD, Eleazar EskiniD, Saharon RossetiD, Sriram SankararamaniD, Eran HalperiniD

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Abstract

We benchmarked two approaches for the detection of cell-type-specific differential DNA methylation: Tensor Composition Analysis (TCA) and a regression model with interaction terms (CellDMC). Our experiments alongside rigorous mathematical explanations show that TCA is superior over CellDMC, thus resolving recent criticisms suggested by Jing et al. Following misconceptions by Jing and colleagues with modelling cell-type-specificity and the application of TCA, we further discuss best practices for performing association studies at cell-type resolution. The scripts for reproducing all of our results and figures are publicly available at github.com/cozygene/CellTypeSpecificMethylationAnalysis.

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65% semantic matchBioinformatics
Jing Han, Shijie Zheng, Charles E. Breeze+2 more·bioRxiv·Feb 28, 2021· 1 citations