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• W2945151194 abstract "Bisulfite DNA methylation sequencing (Methyl-Seq) becomes one of the most important technologies to study methylation level difference at a genome-wide scale. Due to the complexity and large scale of methyl-Seq data, power calculation and study design method have not been developed. Here, we propose a MethylSeqDesign framework for power calculation and study design of Methyl-Seq experiments by utilizing information from pilot data. Differential methylation analysis is based on a beta-binomial model. Power calculation is achieved using mixture model fitting of p-values from pilot data and a parametric bootstrap procedure. To circumvent the issue of existing tens of millions of methylation sites, we focus on the inference of pre-specified targeted regions. The performance of the method was evaluated with simulations. Two real examples are analyzed to illustrate our method. An R package MethylSeqDesign to implement this method is publicly available." @default.
• W2945151194 created "2019-05-29" @default.
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• W2945151194 date "2019-05-20" @default.
• W2945151194 modified "2023-09-25" @default.
• W2945151194 title "MethylSeqDesign: a framework for Methyl-Seq genome-wide power calculation and study design issues" @default.
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• W2945151194 doi "https://doi.org/10.1093/biostatistics/kxz016" @default.
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