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.
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.
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.
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).
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.
A package to predict genes that are differentially spliced between two different conditions using RNA-seq data. This method allows users to detect tissue-specific alternative splicing in brain versus liver samples and tumour stage-specific alternative splicing in neuroblastoma patients. SplicingCompass reduces the number of statistical tests considerably and better accounts for combined effects..
Assists in discovering alternative splicing (AS) events in transcripts predicted from RNA-seq data and in comparing them across multiple conditions. ASprofile is a program that can analyze all pairs of transcripts in the sixteen tissues to determine exons included in one transcript and skipped in the other. To realize these operations, this software is composed of several tools: “extract-as”; “extract-as-fpkm”; and “collect-fpkm”.