Year: 2019
Type: article
Abstract: Epitranscriptome profiling using MeRIP-seq is a powerful technique for in vivo functional studies of reversible RNA modifications. We develop RADAR, a comprehensive analytical tool for detecting differentially methylated loci in MeRIP-seq data. RADAR enables accurate identification of altered methylation sites by accommodating variability of pre-immunoprecipitation expression level and post-immunoprecipitation count using different strategies. In addition, it is compatible with complex study design when covariates need to be incorporated in the analysis. Through simulation and real dataset analyses, we show that RADAR leads to more accurate and reproducible differential methylation analysis results than alternatives, which is available at https://github.com/scottzijiezhang/RADAR.
Source: Genome biology
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,490
Funders: Howard Hughes Medical Institute, Alfred P. Sloan Foundation, Chan Zuckerberg Initiative, National Institutes of Health, National Human Genome Research Institute, National Cancer Institute, National Institute of General Medical Sciences, National Institute of Diabetes and Digestive and Kidney Diseases
OpenAlex ID: W2998099417