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Nat Methods. 2015 Apr;12(4):347-50. doi: 10.1038/nmeth.3314. Epub 2015 Mar 2.

Genome sequence-independent identification of RNA editing sites.

Author information

1
Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, USA.
2
1] Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, USA. [2] Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, USA. [3] Molecular Biology Institute, University of California, Los Angeles, Los Angeles, USA.

Abstract

RNA editing generates post-transcriptional sequence changes that can be deduced from RNA-seq data, but detection typically requires matched genomic sequence or multiple related expression data sets. We developed the GIREMI tool (genome-independent identification of RNA editing by mutual information; https://www.ibp.ucla.edu/research/xiao/GIREMI.html) to predict adenosine-to-inosine editing accurately and sensitively from a single RNA-seq data set of modest sequencing depth. Using GIREMI on existing data, we observed tissue-specific and evolutionary patterns in editing sites in the human population.

PMID:
25730491
PMCID:
PMC4382388
DOI:
10.1038/nmeth.3314
[Indexed for MEDLINE]
Free PMC Article

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