It is important to distinguish differential transcript usage (DTU) from gene-level differential expression and from transcript-level differential expression (DTE). In particular, DTU considers changes in the proportions of the isoforms of a gene that are expressed as opposed to changes of the individual transcript levels. DTU implies DTE but not necessarily the reverse. Although the main transcriptional units of interest are the transcripts, it has been difficult to obtain accurate and precise transcript-level expression estimates due to the extensive overlap between different transcripts. This has prompted researchers to develop alternative ways of representing and analyzing the observed data. One such approach, which has been used as a surrogate for DTU, is differential exon usage (DEU), where data are represented on the level of disjoint counting bins.
Offers a model for alternative splicing (AS) at exon or isoform level. MISO is a program that uses information in single-end or paired-end RNA-seq data and a Bayesian inference to estimate the probability for a read to be issued from a particular isoform. The program is available through two packages: in C language (fastmiso) or in Python language (misopy). The application supplies confidence intervals (CIs) for: (i) estimating of exon and isoform abundance, (ii) identifying differential expression. It can be applied for analyzing isoform regulation.
Analyzes parallel RNA sequence data to catalog transcripts and assess differential and alternative expression of known and predicted mRNA isoforms in cells and tissues. ALEXA-Seq comprises several functions: (1) creation of a database of expression and alternative expression sequence ‘features’, (2) mapping of short paired-end sequence reads to these features, (3) identification of features that are expressed above background noise while taking into account locus-by-locus noise, or (4) identification of features that are differentially expressed in samples.
Allows expression level estimation and differential expression (DE) from RNA-Seq data. IsoEM uses bootstrapping to infer confidence intervals for gene and isoform expression level estimates. The differential expression tool IsoDE, included in the package, performs DE analysis using bootstrap samples generated by IsoEM2. The main feature of these tools is the fast non-parametric computation of confidence intervals and identification of DE genes based on bootstrapping.
A statistical model and computer program designed for detection of differential alternative splicing from replicate RNA-Seq data. rMATS uses a hierarchical model to simultaneously account for sampling uncertainty in individual replicates and variability among replicates. In addition to the analysis of unpaired replicates, rMATS also includes a model specifically designed for paired replicates between sample groups. The hypothesis-testing framework of rMATS is flexible and can assess the statistical significance over any user-defined magnitude of splicing change. The old version of rMATS was called MATS.
An easy-to-use application for microarray, RNA-Seq and metabolomics analysis. For splicing sensitive platforms (RNA-Seq or Affymetrix Exon, Gene and Junction arrays), AltAnalyze will assess alternative exon (known and novel) expression along protein isoforms, domain composition and microRNA targeting. In addition to splicing-sensitive platforms, AltAnalyze provides comprehensive methods for the analysis of other data (RMA summarization, batch-effect removal, QC, statistics, annotation, clustering, network creation, lineage characterization, alternative exon visualization, gene-set enrichment and more).
Supported by the European Molecular Biology Organization [EMBO Installation Grant 3057]; Fundação para a Ciência e a Tecnologia [FCT Investigator Starting Grant IF/00595/2014, PhD Studentship SFRH/BD/131312/2017, project PERSEIDS PTDC/EMS-SIS/0642/2014]; project cofunded by FEDER, via POR Lisboa 2020 - Programa Operacional Regional de Lisboa, from PORTUGAL 2020, and by Fundação para a Ciência e a Tecnologia [LISBOA-01-0145-FEDER-007391].
Allows to analyze differential splicing. SUPPA measures differential splicing between conditions by exploiting the variability between biological replicates to determine the uncertainty in the proportion spliced-in (PSI) values. The software is also able to analyze multiple conditions by computing the pairwise differential splicing between conditions, and can detect groups of events with similar splicing patterns across conditions using density-based clustering.
Tests for differential usage of exons and hence of isoforms in RNA-seq samples. DEXSeq uses generalized linear models and offers reliable control of false discoveries by taking biological variation into account. It also detects with high sensitivity genes, and in many cases exons, that are subject to differential exon usage. DEXSeq achieves reliable control of false discovery rates by estimating variability for each exon or counting bin and good power by sharing dispersion estimation across features.
Detects, quantifies and displays differential splicing between groups of experiments. MAJIQ defines a general concept of local splicing variations (LSVs). It enables users to add previous transcriptome annotation with reliably-detected de-novo junctions from RNA-Seq experiments. This tool can capture all types of alternative splicing (AS) and many other variations which are more complex.
Allows user-friendly automated stage-wise analysis of high-throughput genomic data. stageR implements two-stage testing as a general paradigm for assessing high throughput experiments involving multiple hypotheses that can be aggregated. The procedure was optimized towards RNA-seq applications: differential transcript expression, differential transcript usage and differential gene expression analysis with simple and complex experimental designs. stageR achieves an optimal middle ground between biological resolution and statistical power while providing gene-level false discovery rate (FDR) control, which is beneficial for downstream biological interpretation and validation.
Identifies and analyzes the potential consequences of isoform switches from RNA-seq derived quantification of full-length isoforms. IsoformSwitchAnalyzeR facilitates integration of many sources of annotation including features such as open reading frame (ORF), protein domains, signal peptides, coding potential. Finally, this module also offers article ready visualization of isoform switches as well as multiple layers summary statistics describing the global amount and consequences of isoform switching.
Detects and quantify alternative splicing (AS) events in RNA-Seq experiments. Solas is an R package that is composed of three different functions: (i) DASI (Differential Alternative Splicing Index), for the detection of alternative splicing events differentiating two conditions; (ii) CASI (Cell Alternative Splicing Index), for the identification of genes and exons which are part of an AS event; and (iii) POEM (Proportion Estimation) for the quantification of the relative proportion of different isoforms.
A computational method, robust to biological and technical variability, which identifies significant transcript isoform changes across multiple samples. iso-kTSP reveals novel signatures of cancer in terms of transcript isoforms specifically expressed in tumors, providing novel potential molecular targets for prognosis and therapy.
An R/Bioconductor package that builds on the statistical techniques used by the well-established DEXSeq package to detect differential usage of both exonic regions and splice junctions. In particular, JunctionSeq is capable of detecting differentials in novel splice junctions without the need for an additional isoform assembly step, greatly improving performance when the available transcript annotation is flawed or incomplete. JunctionSeq also provides a powerful and streamlined visualization toolset that allows bioinformaticians to quickly and intuitively interpret their results.
Allows users to predict differential splicing of genes in case-control studies based on the information-theoretic concept of entropy. ARH-seq evaluates the distribution of changes in exon combi-counts by comparing two samples with the information-theoretic concept of entropy. For each exon ARH-seq computes a numerical value that indicates its differential splicing probability so that exons within the gene can be prioritized.
Processes 3’ mRNA sequencing data. expressRNA classifies the sites where cleavage and polyadenylation take place. It is able to identify the differentially regulated poly(A) sites. This tool provides a flexible data integrative research platform. It facilitates highly reproducibility for computational analysis and allows users to visualize and share data and results in a user-friendly way.
Quantifies local exon inclusion levels in paired-end RNA-seq data. SpliceTrap is a method to generates alternative splicing profiles for different splicing patterns, such as exon skipping, alternative 5’ or 3’ splice sites, and intron retention. It relies on RNA-seq and can determine the inclusion level of every exon within a single cellular condition, without requiring a background set of reads.
Provides a one-stop solution for gene expression and alternative splicing (AS) analyses of microarray data. JETTA is an integrated software package that provides many options for array normalization, probe selection, background correction, expression index computation. It also provides the visualization of AS signals. In addition, it is integrated with cisGenome Brower to allow the examination of raw signals of exons and junctions.
Assists users for joint estimation of isoform-level expression and isoform-specific read distribution. Sequgio is a method using RNA-Seq data from multiple samples to estimate the isoforms expression, taking into account non-uniform read distribution. This approach provides substantial improvement on the quality of model fitting and improves the sensitivity in isoform-level differential expression analysis.