Intron retention identification software tools | RNA sequencing data analysis
Alternative splicing (AS) affects up to 95% of multi-exonic genes in humans. The three main types of AS are exon skipping, alternative 5′ or 3′ usage and intron retention (IR). IR occurs when an intron is transcribed into pre-mRNA and remains in the final mRNA. It constitutes a class of AS that is often neglected because these events are difficult to measure reliably.
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.
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.
Identifies correctly intron retention (IR) events and measured the ratio of retained introns to correctly spliced introns with great accuracy. IRFinder was developed to accurately detect IR from mRNA sequencing data. It implements an end-to-end analysis of retained introns from mRNA sequencing data in multiple species. It also includes alignment via the STAR algorithm, quality controls on the sample analyzed, IR detection, and quantification and statistics for comparing IR levels between multiple samples. IRFinder is a part of bioinformatics tools developed by CNRS to study the impact of intron retention on gene regulation.
Analyzes intron retention (IR) in RNA-seq data. KMA was used to study IR in populations of human erythroblasts from proE to orthoE. It performs intron retention estimation and detection using biological replicates and resampling. The tool takes abundance estimation on introns and transcripts and computes statistics on them.
Allows to make intron retention (IR) analysis for erythroid development and erythroid differentiation. Erythroid Intron Retention Analysis was specially designed for RNA-Seq. It was applied to study IR in populations of human erythroblasts from human erythroblast populations-proerythroblasts (proE) to orthochromatophilic erythroblasts (orthoE). The platform offers the post-processing results of the study.
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.
An application written in python that detects and visualizes alternative splicing events using spliced alignments. Sircah takes as input transcript models in the GFF3 format allowing the user the flexibility to choose the sources of evidence for the use in detecting alternative transcription.
A pipeline for the identification of novel exons/alternatively spliced variants (ASVs). ExonFinder is a large-scale comparative analysis of the expressed sequence tag (EST) library from nine grass plants against three crop genomes (rice, maize, and sorghum) and identified 2,879 previously-unannotated exons in the three crops. The library also includes barley (Hordeum vulgare), meadow ryegrass (Festuca pratensis), purple false brome (Brachypodium distachyon), sugarcane (Saccharum officinarum), switchgrass (Panicum virgatum), and wheat (Triticum aestivum).
A supervised machine learning-based approach for IR event detection from RNA-Seq data. IRclassifier chooses J48 Decision Tree and Random Forest as the classification algorithms. IRclassifier is designed to train a model based on the common predicted IR events from MATS, ExpressionPlot and IRFinder, and then classify each candidate as a true or false IR events.
Investigates splice junctions and alternative splicing (AS) events from RNA-Seq data. SplicingViewer provides a platform dedicated to the visualization of AS patterns. The software first aligns short reads to reference genome, then detect of candidate splice junctions, and, lastly align unmapped short reads to splice junctions. It also displays genome mapping and junction mapping reads.
A generalized framework to systematically investigate the synergistic and antagonistic effects of differential splicing and differential expression. dSpliceType detects and prioritizes a list of genes that are differentially expressed and/or spliced. In particular, the multivariate dSpliceType is among the fist to utilize sequential dependency of normalized base-wise read coverage signals and capture biological variability among replicates using a multivariate statistical model.
Sorts alternative splicing (AS) and discovers coding potential. spliceR simplifies downstream sequence analysis by allowing annotation of genomic coordinates of the differentially spliced elements. It is able to detect coding potential of transcripts, determines untranslated region (UTR) and open reading frame (ORF) lengths and predicts whether transcripts are nonsense mediated decay (NMD)-sensitive based on compatible annotated start codon positions and their downstream ORF.
Allows users to extract, annotate and analyze alternative splicing (AS) types for sequence alignment files from RNA-Seq. SplicingTypesAnno can detect the novel splicing directly from the aligned raw reads. This tool assists users in management of large set of data by genome-scale and gene-scale functions. Moreover, for the genome scale annotation users can make use of computer clusters with parallel computing feature to accelerate the multiple sample analysis.
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”.
Simplifies the characterization of genome-wide changes in alternative splicing (AS) under different experimental conditions. ASpli analyzes the differential usage of introns, exons, and splice junctions using read counts. It can estimate the magnitude of changes in AS by computing differences in the percentage of exon inclusion or intron retention using splice junctions. It allows users to produce self-explanatory intermediate outputs, based on the aim of their analysis.
Provides an assortment of methods dedicated to alternative splicing events analysis. ASATP is available as both a standalone software and a web application. It gathers various functions that can be queried separately for (i) identifying and visualizing alternative splicing events; (ii) verifying open reading frame (ORF) changes, (iii) evaluating regulations of alternative splicing and (iv) producing statistical analysis.
Performs intron-exon retention analysis on RNA-seq data. IntEREst facilitates estimation and comparison of splicing efficiency of various transcripts across several samples. It can estimate the intron-retention levels or the exon junction levels in the transcripts. This method determines the intron-retention by counting the number of rna-seq reads that have been mapped to the intron-exon junctions of the genes.
A computational tool for intron retention (IR) event detection from RNA-Seq data. IRcall calculates the IRscore, which combines information on three aspects: (a) ratio of RPKM within an intron to flanking exons; (b) ratio of read counts within an intron to read counts supporting splice junctions; (c) read coverage within an intron. The introns are ranked by IRscores in descending order, with top-n% introns returned as IR events. Note that top-n% is the user-specified threshold (default top-100%).
Serves for the detection of genome-wide. iREAD works with both single-end and paired-end sequencing data that has been prepared using poly-A enrichment. The resulting intron retention contents can be explored in various ways such as functional enrichment and differential expression. It represents a generic tool to interrogate the previously largely neglected intronic regions from the angle of view of intron retention.