RNA editing site identification software tools | RNA sequencing data analysis

Detects RNA editing by learning and summarizing essential features from the surrounding primitive sequence of candidate single nucleotide variants (SNVs). DeepRed is a program that can serve for discovering the developmental pattern of RNA editing changes during human early embryogenesis. It also can be used for exploring the evolutionary pattern of RNA editing in the primate lineage and Drosophila species.

Performs investigation of RNA editing from next-generation sequencing (NGS) data. REDItools contains three main scripts to study RNA editing using both RNA-Seq and DNA-Seq data from the same sample/individual or RNA-Seq data alone: (1) REDItoolDnaRNA.py for detecting RNA editing candidates, (2) REDItoolKnown.py for exploring the RNA editing potential of RNA-Seq experiments, and (3) REDItoolDenovo.py for performing de novo detection of RNA editing candidates. It also includes some accessory scripts and allows to annotate all candidate positions using relevant databases.

Assists users to predict adenosine-to-inosine editing from a single RNA-Seq data set. GIREMI can separate the RNA editing sites from genomic variations (such as single nucleotide polymorphisms (SNPs)) based on single RNA-Seq datasets. This program processes by determining the RNA-editing sites from a list of credible single nucleotide variants (SNVs) with known SNPs and the corresponding bam file.

AnalyzeS RNA editing events from RNA sequencing data. RNAEditor maps the reads to the genome, calculates sequence variations, filters for “non-editing sites” and applies a cluster algorithm to detect highly edited sites (“editing islands”), which indicates potential ADAR binding sites, gives higher confidence that the contained editing sites are ‘true’ editing sites and higher likelihood of biological importance. RNAEditor is valuable to detect RNA editing events from RNA-seq data without for additional experimental techniques.

Allows users to analyze U-indel RNA editing in non-model species with no prior data available. T-Aligner is a read mapping and assembly tool that fits multiple potential edited open reading frames (ORFs) from shotgun reads mapped to each cryptogene. The application enables the read mapping and visualization of the totality of the editing states and their coverage as well as the assembly of canonical and alternative translatable mRNAs.