Novel isoform quantification software tools | RNA sequencing data analysis
RNA-Seq is being increasingly adopted as the technology of choice for gene expression studies, and with large numbers of experiments producing partial transcripts of genes, it is expected that there will be rapid progress in the coming years in annotating genomes. As more complete genome annotations are produced, it is increasingly desirable to include them in analyses rather than assembling transcripts ‘from scratch’ with every new experiment. The reference annotation-based transcript assembly approach we have introduced addresses this problem, and allows for the incremental improvement of annotations with RNA-Seq experiments. It is also convenient in that novel genes and transcripts (with respect to an existing annotation) are easily extracted from the output of our assembler.
Assembles transcripts, estimates their abundances, and tests for differential expression and regulation in RNA-Seq samples. Cufflinks assembles individual transcripts from RNA-seq reads that have been aligned to the genome. This software is able to infer the splicing structure of each gene because reads from multiple splice variants for a given gene can be found in a sample. Quantification of transcript abundances is also possible by preferring a reference annotation to assembling the reads.
Allows users to handle RNA-sequencing pipeline based on the TopHat, Cufflinks and CummeRbund suite of software. Tuxedo is a program that enables assessment of alternative splicing (AS) inferred on fragments per kilobase per million (FPKM) values. It can assist researchers to detect genes and splicing variants and compare gene expression and transcripts under different conditions.
Provides analysis, management and visualization tools for next-generation sequencing (NGS) data. Strand NGS supports extensive workflows for alignment, RNA-seq, small RNA-seq, DNA-seq, Methyl-seq, MeDIP-seq and ChIP-seq experiments. This tool includes standard differential expression analysis for different experimental conditions, as well as differential splicing analysis. It can notice variants in the transcriptome and gene fusion events.
A comprehensive and user-friendly system for computational analysis of bacterial RNA-seq data. As input, Rockhopper takes RNA sequencing reads output by high-throughput sequencing technology (FASTQ, QSEQ, FASTA, SAM, or BAM files). Rockhopper supports the following tasks: reference based transcript assembly; de novo transcript assembly; normalizing data from different experiments; quantifying transcript abundance; testing for differential gene expression; characterizing operon structures; visualizing results in a genome browser.
Enables reconstruction of a transcriptome from RNA-seq reads. StringTie uses a genome-guided transcriptome assembly approach along with concepts from de novo genome assembly to improve transcript assembly. Successively this tool: first groups the reads into clusters, then creates a splice graph for each cluster from which it identifies transcripts, and then for each transcript it creates a separate flow network to estimate its expression level.
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).
Serves as a transcriptome reconstruction method. Scripture is able to reconstruct a mammalian transcriptome with no prior knowledge of gene annotations. It exploits longer reads that span splice junctions to link discontiguous (spliced) segments. This software identifies short but strongly expressed transcripts, lower transcripts with aggregate evidence and precise gene structures for most of found lincRNA loci.