MACS was originally designed to give robust and high resolution peak identification for ChIP-Seq data. It can also be used to identify peak for MeRIP-Seq data.
The exomePeak R-package has been developed based on the MATLAB exomePeak package, for the analysis of RNA epitranscriptome sequencing data with affinity-based shotgun sequencing approach, such as MeRIP-Seq or m6A-Seq.
MeTPeak is a graphical model-based peak calling method for transcriptome-wide detection of m6A sites from MeRIP-seq data. MeTPeak explicitly models read count of an m6A site and introduces a hierarchical layer of Beta variables to capture the variances and a Hidden Markov model to characterize the reads dependency across a site.
BayesPeak is a Bioconductor package for the analysis of data sets from ChIP-seq experiments, particularly for identifying the genomic sites of protein–DNA interactions. It can also be used to identify RNA modification peak for MeRIP-Seq data.
m6aViewer is a cross-platform application for analysis and visualization of m6A peaks from sequencing data. m6aViewer implements a novel m6A peak-calling algorithm that identifies high-confidence methylated residues with more precision than previously described approaches.
PEA is an integrated R toolkit to facilitate the analysis of plant epitranscriptome data. The PEA toolkit contains a comprehensive collection of functions required for read mapping, CMR calling, motif scanning and discovery and gene functional enrichment analysis.
RNA modification predictors ( Diverse modifications) Specific modification
The RNAMethPre web server provides a user-friendly tool for the prediction and query of mRNA m6A sites.
HAMR (High-throughput Annotation of Modified Ribonucleotides) is a web application that can not only locate these modifications transcriptome-wide with single nucleotide resolution in RNA-seq data, but can also differentiate between different classes of modifications.
RNAm5Cfinder is a web-server that is based on RNA sequence features and machine learning method to predict RNA m5C sites in eight tissue/cell types from mouse and human.
WHISTLE is a prediction framework for transcriptome-wide m6A RNA-methylation site prediction. A web server was built to facilitate the query of their high-accuracy map of the human m6A epitranscriptome predicted by WHISTLE.
DeepM6ASeq is a deep-learning-based framework to predict m6A-containing sequences and visualize saliency map for sequences.
BERMP is a web server that could predict multi-species m6A sites from nucleotide sequences. It integrates a classifier based on random forest with the encoding of extended nucleic acid content and a deep-learning classifier based on bidirectional Gated Recurrent Units. BERMP performs better than existing m6A classifiers for different species.
SRAMP is a a mammalian m6A sites predictor which can extract and integrate the sequence and predicted structural features around m6A sites under a machine learning framework.
RFAthM6A is tool for predicting m6A sites in Arabidopsis thaliana based on manually curated a reliable dataset of m6A sites and non-m6A sites.
iRNA-Methyl is a web server for identifying N6- methyladenosine sites using pseudo nucleotide composition.
iRNA-2methyl is a web server for identifying RNA 2'-O-methylation Sites by Incorporating Sequence-Coupled Effects into General PseKNC and Ensemble Classifier.
PseUI was developed by using support vector machine based on three different kinds of features including position specific nucleotide propensity, nucleotide composition, and Pseudo nucleotide composition. Now it is for three different species including H. sapiens, M. musculus and S. cerevisiae.
RAM-NPPS is a sequence predictor for identifying N6-methyladenosine sites using multi-interval nucleotide pair position specificity and support vector machine.
MethyRNA is a sequence-based tool for the identification of N6-methyladenosine sites
HMpre is a mRNA N6-Methylation predictor for human, which exhibits good performance and robustness, owing to training on the whole dataset without sampling noise.
PEA-m5C is a machine learning-based m5C predictor trained with features extracted from the flanking sequence of m5C modifications.
M5C-HPCR is a m5C site predictor by introducing a novel heuristic nucleotide physicochemical property reduction (HPCR) algorithm and classifier ensemble.
AthMethPre is a web server for the prediction and query of mRNA m6A sites in Arabidopsis thaliana.
M6APred-EL is a a Sequence-Based Predictor for Identifying N6-methyladenosine Sites Using Ensemble Learning.
m6ASNP is a user-friendly web server that is dedicated to the identification of genetic variants that target m6A modification sites.
pRNAm-PC is a tool for predicting N(6)-methyladenosine sites in RNA sequences via physical-chemical properties.
PPUS is a web server to predict PUS-specific pseudouridine sites.
RNA modification database ( Diverse modifications) Specific modification
MODOMICS is a database of RNA modifications that provides comprehensive information concerning the chemical structures of modified ribonucleosides, their biosynthetic pathways, the location of modified residues in RNA sequences, and RNA-modifying enzymes.
RMBase (RNA Modification Base) is designed for decoding the landscape of RNA modifications identified from high-throughput sequencing data (MeRIP-seq, m6A-seq, miCLIP, m6A-CLIP, Pseudo-seq, Ψ-seq, CeU-seq, Aza-IP, RiboMeth-seq). It contains ~124200 N6-Methyladenosines (m6A), ~9500 pseudouridine (Ψ) modifications, ~1000 5-methylcytosine (m5C) modifications, ~1210 2′-O-methylations (2′-O-Me) and ~3130 other types of RNA modifications.
RNAMDB has served as a focal point for information pertaining to naturally occurring RNA modifications. In its current state, the database employs an easy-to-use, searchable interface for obtaining detailed data on the 109 currently known RNA modifications. Each entry provides the chemical structure, common name and symbol, elemental composition and mass, CA registry numbers and index name, phylogenetic source, type of RNA species in which it is found, and references to the first reported structure determination and synthesis.
MeT-DB was the first comprehensive database focusing on N6-methyladenosine (m6A) methyltranscriptome. MeT-DB V2.0 is the significantly improved and redesigned version that focuses more on elucidating context-specific m6A functions.
m6AVar is a comprehensive database of m6A-associated variants that potentially influence m6A modification, which will help to interpret variants by m6A function. The m6A-associated variants were derived from three different m6A sources including miCLIP/PA-m6A-seq experiments (high confidence), MeRIP-Seq experiments (medium confidence) and transcriptome-wide predictions (low confidence).
RNAModR provides functions to map lists of genomic loci of RNA modifications to a reference mRNA transcriptome, and perform exploratory functional analyses of sites across the transcriptome trough visualisation and statistical analysis of the distribution of sites across transcriptome sections (5'UTR, CDS, 3'UTR).
The package is designed for transcriptomic visualization of RNA-related genomic features represented with genome-based coordinates with respect to the landmarks of RNA transcripts.
RCAS is an R/Bioconductor package designed as a generic reporting tool for the functional analysis of transcriptome-wide regions of interest detected by high-throughput experiments. Such transcriptomic regions could be, for instance, signal peaks detected by CLIP-Seq analysis for protein-RNA interaction sites, RNA modification sites (alias the epitranscriptome), CAGE-tag locations, or any other collection of query regions at the level of the transcriptome.
RNA modification high-throughput technologies ( Diverse modifications)
ICE followed by NGS identifies adenosine-to-inosine editing. In this method, RNA is treated with acrylonitrile, while control RNA is untreated. Control and treated RNAs are reverse-transcribed and PCR-amplified. Inosines in RNA fragments treated with acrylonitrile cannot be reverse-transcribed. Deep sequencing of the cDNA prepared from control and treated RNA provides high-resolution reads of inosines in RNA fragments.
MeRIP-Seq (Methylated RNA Immunoprecipitation Sequencing) maps methylated RNA. In this method, modification-specific antibodies are used to immunoprecipitate RNA. RNA is reverse-transcribed to cDNA and sequenced. Deep sequencing provides high-resolution reads of methylated RNA.
miCLIP-m6A (m6A Individual-Nucleotide-Resolution Crosslinking and Immunoprecipitation) maps m6A locations in the transcriptome with single-nucleotide resolution. In this method, anti-m6A antibodies are crosslinked to mRNA sequences, and a cDNA library is prepared and sequenced. The cDNA library preparation in miCLIP follows the iCLIP protocol closely.
PA-m6A-seq is a photo-crosslinking-assisted m6A sequencing strategy to more accurately define sites with m6A modification.
m6A-LAIC-seq (m6A-level and isoform-characterization sequencing) is a method to quantify transcript copies of particular genes with m6A modified ('m6A levels') or the relationship of m6A modification(s) to alternative RNA isoforms.
Bisulfite-seq can be used to map modified cytosine sites across a human transcriptome
m5C-RIP (m5C RNA immunoprecipitation)
Aza-IP (5-azacytidine–mediated RNA immunoprecipitation) exploits the catalytic mechanisms of the m5C methyltransferases to covalently link methyltransferase to its RNA targets. First, the cytidine analog 5-azacytidine is randomly incorporated into the nascent RNA of cells overexpressing an epitope-tagged m5C RNA methyltransferase. Due to the nitrogen substitution at the C5 position, a stable covalent bond forms when the RNA methyltransferase attacks the C6 position of its RNA targets. These targets are enriched by immunoprecipitation and subsequently sequenced.
Ψ-seq is a method to transcriptome-wide quantitative mapping of Ψ, which has been used to identify the vast majority of Ψ sites in rRNA, tRNA and snRNA and dozens of novel sites within snoRNAs and mRNAs.
CeU-Seq (N3-CMC-enriched pseudouridine sequencing) is a selective chemical labeling and pulldown method, which identified 2,084 Ψ sites within 1,929 human transcripts.
Pseudo-Seq detects pseudouridylation sites in ncRNAs with single-nucleotide resolution using high-throughput sequencing. Pseudo-Seq is very similar to PSI-seq, in that both methods use CMC to modify pseudouridines selectively and halt reverse transcription. However, Pseudo-Seq circularizes cDNA strands before PCR amplification and purification, instead of using ARTseq.
PSI-Seq (Pseudouridine Site Identification Sequencing) identifies RNA sequences containing pseudouridine sites using high-throughput sequencing. PSI-Seq uses N-Cyclohexyl-N_-(2-morpholinoethyl)carbodiimide (CMC) to modify pseudouridines selectively, effectively halting reverse transcription. The cDNA libraries are prepared by the ARTseq method.
m1A-seq is based on methylated RNA immunoprecipitation sequencing (MeRIP-seq), which is used for transcriptome-wide localization of m1A sites and coupled it to an orthogonal chemical method based on Dimroth rearrangement to obtain high-resolution m1A maps
m1A-ID-seq technique is based on m1A immunoprecipitation and the inherent ability of m1A to stall reverse transcription, as a means for transcriptome-wide m1A profiling.
TRAC-seq is m7G methylated tRNA immunoprecipitation sequencing (MeRIP-seq) and tRNA reduction and cleavage sequencing to reveal the m7G tRNA methylome
AlkAniline-Seq is a new principle of RNAseq library preparation, which relies on a chemistry based positive enrichment of reads in the resulting libraries, and therefore leads to unprecedented signal-to-noise ratios. It enables a deep sequencing-based technology for the simultaneous detection of 7-methylguanosine (m7G) and 3-methylcytidine (m3C) in RNA at single nucleotide resolution.
ChIPseeker is a Bioconductor package implements functions to retrieve the nearest genes around the peak, annotate genomic region of the peak, statstical methods for estimate the significance of overlap among ChIP peak data sets.
The Rfam database is a collection of RNA families, each represented by multiple sequence alignments, consensus secondary structures and covariance models (CMs).
ENCODE is a public research consortium aimed at identifying all functional elements in the human and mouse genomes.
POSTAR is a resource of POST-trAnscriptional Regulation coordinated by RNA-binding proteins (RBPs). Based on new studies and resources, POSTAR supplies the largest collection of experimentally probed (~23 million) and computationally predicted (approximately 117 million) RBP binding sites in the human and mouse transcriptomes.