A protocol for RNA methylation differential analysis with MeRIP-Seq data and exomePeak R/Bioconductor package.
By Jia Meng, Zhiliang Lu, Hui Liu, Lin Zhang, Shaowu Zhang, Yidong Chen, M. Rao, Yufei Huang. Methods, 2014
330 citations recorded by the source corpus.
Subfields: Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/b401f84e34ad3bbbdfed2282b5cb4ef94291ab55
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In Molecular Biology
Citations in the corpus
- Small-molecule targeting of oncogenic FTO demethylase in acute myeloid leukemia (2019, methodology): “exomePeak (Meng et al., 2014) with default setting was used to m6A peak calling and Integrative Genomics Viewer (IGV) (Robinson et al.”
- A novel algorithm for calling mRNA m6A peaks by modeling biological variances in MeRIP-seq data (2016, methodology): “Particularly, a number of beta distributions of peak regions with variances designed to range from 0.014 to an extreme high level 0.134, corresponding to a ; b ½ (cid:2) ¼ 0 : 3 ; 0 : 1 ½ ; were simulated to generate reads, where p mean ¼ 0 : 75 was held for each case.”
- Zc3h13 regulates nuclear RNA m6A methylation and mouse embryonic stem cell self-renewal (2018, methodology): “0.12b) (Trapnell et al., 2009) under parameters: “--max-multihits 1 --prefilter-multihits” and “--transcriptome-index”. m6A peaks were identified using exomePeak R/Bioconductor package with default parameters (Meng et al., 2014).”
- METTL14 Inhibits Hematopoietic Stem/Progenitor Differentiation and Promotes Leukemogenesis via mRNA m6A Modification (2017, unknown): “8.0 (Meng et al., 2014) http://bioconductor.org/packages/release/ bioc/html/exomePeak.html GSEA-2.”