RED-ML specifications


Unique identifier OMICS_17323
Alternative name RNA Editing Detection based on Machine Learning
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data The input to RED-ML can be as simple as a single BAM file, while it can also take advantage of matched genomic variant information when available.
Input format BAM
Output data The output not only contains detected RNA editing sites, but also a confidence score to facilitate downstream filtering.
Operating system Unix/Linux
Programming languages C++, Perl
License GNU General Public License version 3.0
Computer skills Advanced
Stability Stable
Requirements SAMtools package, Perl modules: FindBin, Getopt::Long, File::Basename
Maintained Yes



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  • person_outline Leo Lee <>

Publication for RNA Editing Detection based on Machine Learning

RED-ML institution(s)
BGI-Shenzhen, Shenzhen, China; China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, China; Department of Urology, Shanghai Changhai Hospital, Second Military Medical University, Shanghai, China; Department of Biology, University of Copenhagen, Copenhagen, Denmark; James D. Watson Institute of Genome Sciences, Hangzhou, China; Department of Electrical and Computer Engineering, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
RED-ML funding source(s)
This project was supported by the Shenzhen Peacock Plan (NO.KQTD20150330171505310).

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