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PMID: 23589649 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Exome-based analysis for RNA epigenome sequencing data.

Bioinformatics (Oxford, England) ·Vol. 29 ·No. 12 ·2013-06-15 ·Pages 1565-7

Meng J, Cui X, Rao MK, Chen Y, Huang Y

Abstract

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. 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. The MATLAB package 'exomePeak' and additional details are available at http://compgenomics.utsa.edu/exomePeak/.

MeSH Terms
Epigenesis, Genetic Exome HEK293 Cells Humans Immunoprecipitation/methods RNA Processing, Post-Transcriptional Sequence Analysis, RNA/methods Software Transcriptome
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
Meng Jia
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
Cui Xiaodong
Rao Manjeet K
Chen Yidong
Huang Yufei
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Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4811
Published
2013-06-15
Epub
2013-00-14
Pages
1565-7
Language
English
Region
England
NLM ID
9808944
PMCID
PMC3673212
Subset
IM
Grants
NCRR NIH HHS · 5G12RR013646-12 · United States
NCI NIH HHS · P30CA54174 · United States
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