
Abstract Motivation: Fragmented RNA immunoprecipitation combined with RNA sequencing enabled the unbiased study of RNA epigenome at a near single-base resolution; however, unique features of this new type of data call for novel computational techniques. Result: Through examining the connections of RNA epigenome sequencing data with two well-studied data types, ChIP-Seq and RNA-Seq, we unveiled the salient characteristics of this new data type. The computational strategies were discussed accordingly, and a novel data processing pipeline was proposed that combines several existing tools with a newly developed exome-based approach ‘exomePeak’ for detecting, representing and visualizing the post-transcriptional RNA modification sites on the transcriptome. Availability: The MATLAB package ‘exomePeak’ and additional details are available at http://compgenomics.utsa.edu/exomePeak/. Contact: yufei.huang@utsa.edu or jmeng@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online.
HEK293 Cells, Sequence Analysis, RNA, Humans, Immunoprecipitation, Exome, RNA Processing, Post-Transcriptional, Transcriptome, Software, Epigenesis, Genetic
HEK293 Cells, Sequence Analysis, RNA, Humans, Immunoprecipitation, Exome, RNA Processing, Post-Transcriptional, Transcriptome, Software, Epigenesis, Genetic
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