Investigating RNA Editing in Deep Transcriptome Datasets With REDItools and REDIportal

Nat Protoc. 2020 Mar;15(3):1098-1131. doi: 10.1038/s41596-019-0279-7. Epub 2020 Jan 29.


RNA editing is a widespread post-transcriptional mechanism able to modify transcripts through insertions/deletions or base substitutions. It is prominent in mammals, in which millions of adenosines are deaminated to inosines by members of the ADAR family of enzymes. A-to-I RNA editing has a plethora of biological functions, but its detection in large-scale transcriptome datasets is still an unsolved computational task. To this aim, we developed REDItools, the first software package devoted to the RNA editing profiling in RNA-sequencing (RNAseq) data. It has been successfully used in human transcriptomes, proving the tissue and cell type specificity of RNA editing as well as its pervasive nature. Outcomes from large-scale REDItools analyses on human RNAseq data have been collected in our specialized REDIportal database, containing more than 4.5 million events. Here we describe in detail two bioinformatic procedures based on our computational resources, REDItools and REDIportal. In the first procedure, we outline a workflow to detect RNA editing in the human cell line NA12878, for which transcriptome and whole genome data are available. In the second procedure, we show how to identify dysregulated editing at specific recoding sites in post-mortem brain samples of Huntington disease donors. On a 64-bit computer running Linux with ≥32 GB of random-access memory (RAM), both procedures should take ~76 h, using 4 to 24 cores. Our protocols have been designed to investigate RNA editing in different organisms with available transcriptomic and/or genomic reads. Scripts to complete both procedures and a docker image are available at

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Base Sequence
  • Brain
  • Computational Biology / methods
  • Databases, Genetic*
  • Genome, Human
  • High-Throughput Nucleotide Sequencing / methods
  • Humans
  • Huntington Disease / genetics
  • Huntington Disease / pathology
  • RNA Editing*
  • Sequence Analysis, RNA
  • Software*