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BioinformaticsPLoS Computational Biology
Peer-reviewed journal article

magpie: a power evaluation method for differential RNA methylation analysis in N6-methyladenosine sequencing

Zhenxing GuoiD, Daoyu DuaniD, Wen TangiD, Julia Zhu, William S. BushiD, Liangliang ZhangiD, Xiaofeng ZhuiD, Fulai JiniD, Hao FengiD

Abstract

MotivationRecently, novel biotechnologies to quantify RNA modifications became an increasingly popular choice for researchers who study epitran-scriptome. When studying RNA methylations such as N6-methyladenosine (m6A), researchers need to make several decisions in its experimental design, especially the sample size and a proper statistical power. Due to the complexity and high-throughput nature of m6A sequencing measurements, methods for power calculation and study design are still currently unavailable. ResultsWe propose a statistical power assessment tool, magpie, for power calculation and experimental design for epitranscriptome studies using m6A sequencing data. Our simulation-based power assessment tool will borrow information from real pilot data, and inspect various influential factors including sample size, sequencing depth, effect size, and basal expression ranges. We integrate two modules in magpie: (i) a flexible and realistic simulator module to synthesize m6A sequencing data based on real data; and (ii) a power assessment module to examine a set of comprehensive evaluation metrics. AvailabilityThe proposed power assessment tool magpie is publicly available as a R/Bioconductor package at: https://bioconductor.org/packages/magpie/.

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