ShapeMapper converts raw sequencing files into mutational profiles, creates SHAPE reactivity plots, and provides extensive diagnostic information useful for experiment analysis and troubleshooting. SuperFold is a pipeline that then uses these data to model RNA secondary structures, including pseudoknots; identify de novo regions with well-defined and stable structures; and visualize most probable and alternative helices.

Detects structured noncoding RNAs in comparative genomics data. RNAz is a program for predicting structurally conserved and thermodynamically stable RNA secondary structures in multiple sequence alignments. It can be used in genome wide screens to detect functional RNA structures, as found in noncoding RNAs (ncRNAs) and cis-acting regulatory elements of messenger RNAs (mRNAs). The algorithm allows to calculate thermodynamic stability scores based on a dinucleotide background model.

Enables non-specialists to easily predict RNA secondary structures using cutting-edge high-throughput structure-probing data. Users can easily access and incorporate these data into the RNAex server to enhance the RNA secondary structure prediction using four different folding methods (MaxExpect, SeqFold, RNAstructure (Fold) and RNAfold). RNAex results allow users to clearly view, identify and understand SNP and post-transcriptional regulation sites on the RNA structures. Overall, the server is an early web-based platform for the emerging new field of high-throughput RNA structure-probing analysis.

A tool for RNA secondary structure prediction with multiple types of experimental probing data. RME can use experimental pairing probabilities to restrain the partition function, and predict the structure with maximum restrained expected accuracy based on a MEA algorithm, MaxExpect. It also provides preprocessing scripts for transforming the SHAPE, PARS and DMS-seq data into pairing probability according a posterior probabilistic model. Moreover, it also contains a utility for optimizing the parameters of RME by RME-Optimize.

An easy-to-use web application that allows the user to visualize RNA-seq data and other genomic annotations on RNA secondary structures. SAVoR is designed to help researchers visualize sequencing data in the context of RNA secondary structures.

Makes possible single-molecule RNA structure analysis by detecting multiple sites of chemical modification in single RNA strands using massively parallel sequencing. RING-MaP single-molecule nucleic acid structure interrogation enables concise and facile analysis of the global architectures and multiple conformations that govern function in RNA.

Provides an integrated computational solution designed specifically for large-scale RNA structure mapping and reconstruction across any transcriptome. StructureFold automates the processing and analysis of raw high-throughput RNA structure profiling data, allowing the seamless incorporation of wet-bench structural information from chemical probes and/or ribonucleases to restrain RNA secondary structure prediction via the RNAstructure and ViennaRNA package algorithms. StructureFold performs reads mapping and alignment, normalization and reactivity derivation, and RNA structure prediction in a single user-friendly web interface or via local installation. StructureFold is freely available as a component of Galaxy.

Deals with RNA structure probing and post-transcriptional modifications mapping high-throughput data. RNA Framework is a modular toolkit. Its main features are (i) automatic reference transcriptome creation, (ii) automatic reads preprocessing (adapter clipping and trimming) and mapping, (iii) scoring and data normalization and (iv) accurate RNA folding prediction by incorporating structural probing data. It can perform not only RNA Structure analysis, but also analysis of RNA post-transcriptional modifications mapping experiments (such as m1A-seq, m6A-seq, 2OMe-seq, and Pseudo-seq).

A visual and interactive application that makes it easy and efficient to gauge data quality, screen for transcripts with high-quality information and identify discordant replicates in structure profiling experiments. SEQualyzer rely on features common to a wide range of protocols and can serve as standards for quality control and analyses. Its outputs permit easy quality evaluation and identification of discordant replicates.

Methods for statistically modeling these structure-probing data and extracting structural features from them.

A probabilistic method for RNA secondary structure prediction that integrates experimental structure probing data. It can be automatically trained given a set of known structures with probing data. The approach is demonstrated on SHAPE data sets, where we evaluate and selectively model specific correlations. The approach often makes superior use of the probing data signal compared to other methods. We illustrate the use of ProbFold on multiple data types using both simulations and a small set of structures with both SHAPE, DMS, and CMCT data. Technically, the approach combines stochastic context-free grammars (SCFGs) with probabilistic graphical models. This approach allows rapid adaptation and integration of new probing data types.

Allows the identification of domains and structures in RNA sequences. MIMEAnTo evaluates MIME data, following error-correction, statistical ascertainment and quality assessment. MIMEAnTo has a wizard-like graphical user interface, guiding through the data analysis procedure in three steps: (i) data input and assessment, (ii) sequencing and reverse transcription error correction and (iii) quantification of raw effects and quality filtering.

A data analysis pipeline for assaying the structure of RNAs by high-throughput sequencing. This technique can be utilized both in vivo and in vitro, with any small molecule that modifies RNA and consequently impedes reverse transcriptase.

An approach to incorporate the reactivities from high-throughput RNA structure probing into ncRNA homology search for functional annotation. By incorporating high-throughput sequencing-based structure probing information, ProbeAlign can improve the accuracy and efficiency of ncRNA homology search. It is a promising tool for ncRNA functional annotation on genome-wide datasets.

Allows high throughput and sample multiplexing. nextPARS is based on the parallel specific enzymatic digestion of single-stranded and double-stranded regions. It is able to tag all four bases in a genome-wide scale, enabling multiplexing in Illumina's sequencing technology. This tool does not enable the ligation first of the 5’adaptor and then the 3’adaptor, requiring the performance of phosphatase and kinase treatments of the RNA ends.

Processes reads and calculates SHAPE reactivities for SHAPE-Seq experiments on multiple RNAs. The Spats package implements a read mapping and reactivity analysis pipeline for calculating SHAPE-Seq reactivities from an input set of next-generation reads. It accepts raw paired-end sequencing reads in fastq format, and a target sequence file containing the sequences of RNAs present in the experimental pool. Spats then performs read alignment to calculate distributions of read ends in the SHAPE (+) and (-) channel for each nucleotide in each RNA. Spats then estimates nucleotide resolution SHAPE reactivities for each RNA, using a model-driven maximum likelihood procedure based on a model of the reverse transcriptase process used in the SHAPE-Seq experiment.

Predicts RNA secondary structure incorporating current high-throughput RNA structure profiling data, such as PARS, FragSeq, SHAPE-Seq, and conventional SHAPE data. SeqFold was applied to predict RNA secondary structures of the yeast transcriptome. Analysis of the structural profile output of SeqFold reveals the diverse roles of RNA secondary structure in translation efficiency, transcription initiation, and identification of RNA binding protein (RBP) targets.