title: Exome-based analysis for RNA epigenome sequencing data.
abstract: BACKGROUND
  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.
  
  
  RESULTS
  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.
  
  
  BACKGROUND
  The MATLAB package 'exomePeak' and additional details are available at http://compgenomics.utsa.edu/exomePeak/.
authors.affiliation: Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, MA 02139, USA. jmeng@mit.edu
authors.forename: Jia
authors.initials: J
authors.lastname: Meng
authors.forename: Xiaodong
authors.initials: X
authors.lastname: Cui
authors.forename: Manjeet K
authors.initials: MK
authors.lastname: Rao
authors.forename: Yidong
authors.initials: Y
authors.lastname: Chen
authors.forename: Yufei
authors.initials: Y
authors.lastname: Huang
mesh_terms: D044127:Epigenesis, Genetic; D059472:Exome; D057809:HEK293 Cells; D006801:Humans; D047468:Immunoprecipitation / Q000379:methods; D012323:RNA Processing, Post-Transcriptional; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software; D059467:Transcriptome