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RADAR: differential analysis of MeRIP-seq data with a random effect model

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 methyl...

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Autores principales: Zhang, Zijie, Zhan, Qi, Eckert, Mark, Zhu, Allen, Chryplewicz, Agnieszka, De Jesus, Dario F., Ren, Decheng, Kulkarni, Rohit N., Lengyel, Ernst, He, Chuan, Chen, Mengjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6927177/
https://www.ncbi.nlm.nih.gov/pubmed/31870409
http://dx.doi.org/10.1186/s13059-019-1915-9
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author Zhang, Zijie
Zhan, Qi
Eckert, Mark
Zhu, Allen
Chryplewicz, Agnieszka
De Jesus, Dario F.
Ren, Decheng
Kulkarni, Rohit N.
Lengyel, Ernst
He, Chuan
Chen, Mengjie
author_facet Zhang, Zijie
Zhan, Qi
Eckert, Mark
Zhu, Allen
Chryplewicz, Agnieszka
De Jesus, Dario F.
Ren, Decheng
Kulkarni, Rohit N.
Lengyel, Ernst
He, Chuan
Chen, Mengjie
author_sort Zhang, Zijie
collection PubMed
description 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.
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spelling pubmed-69271772019-12-30 RADAR: differential analysis of MeRIP-seq data with a random effect model Zhang, Zijie Zhan, Qi Eckert, Mark Zhu, Allen Chryplewicz, Agnieszka De Jesus, Dario F. Ren, Decheng Kulkarni, Rohit N. Lengyel, Ernst He, Chuan Chen, Mengjie Genome Biol Method 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. BioMed Central 2019-12-23 /pmc/articles/PMC6927177/ /pubmed/31870409 http://dx.doi.org/10.1186/s13059-019-1915-9 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Method
Zhang, Zijie
Zhan, Qi
Eckert, Mark
Zhu, Allen
Chryplewicz, Agnieszka
De Jesus, Dario F.
Ren, Decheng
Kulkarni, Rohit N.
Lengyel, Ernst
He, Chuan
Chen, Mengjie
RADAR: differential analysis of MeRIP-seq data with a random effect model
title RADAR: differential analysis of MeRIP-seq data with a random effect model
title_full RADAR: differential analysis of MeRIP-seq data with a random effect model
title_fullStr RADAR: differential analysis of MeRIP-seq data with a random effect model
title_full_unstemmed RADAR: differential analysis of MeRIP-seq data with a random effect model
title_short RADAR: differential analysis of MeRIP-seq data with a random effect model
title_sort radar: differential analysis of merip-seq data with a random effect model
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6927177/
https://www.ncbi.nlm.nih.gov/pubmed/31870409
http://dx.doi.org/10.1186/s13059-019-1915-9
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