Abstract
We developed a computational framework to robustly identify RNA editing sites using transcriptome and genome deep-sequencing data from the same individual. As compared with previous methods, our approach identified a large number of Alu and non-Alu RNA editing sites with high specificity. We also found that editing of non-Alu sites appears to be dependent on nearby edited Alu sites, possibly through the locally formed double-stranded RNA structure.
Original language | English |
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Pages (from-to) | 579-581 |
Number of pages | 3 |
Journal | Nature Methods |
Volume | 9 |
Issue number | 6 |
DOIs | |
Publication status | Published - Jun 2012 |
Externally published | Yes |
ASJC Scopus Subject Areas
- Biotechnology
- Biochemistry
- Molecular Biology
- Cell Biology