1 - 50 of 101 results

STAR / Spliced Transcripts Alignment to a Reference

star_border star_border star_border star_border star_border
star star star star star
Aligns high-throughput long and short RNA-seq data to a reference genome using uncompressed suffix arrays. STAR is a standalone software capable of align reads in a continuous streaming mode. The application first run a seed search for then perform seed clustering and stitching. It is able to detect canonical junctions, non-canonical splices and chimeric transcripts and to map full-length RNA sequences.


star_border star_border star_border star_border star_border
star star star star star
Aligns RNA-Seq reads to mammalian-sized genomes using the ultra high-throughput short read aligner Bowtie. TopHat also analyzes the mapping results to identify splice junctions between exons. It can align reads of various lengths produced by the latest sequencing technologies, while allowing for variable-length indels with respect to the reference genome. The tool combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes.

GEM mapper / GEnome Multitool mapper

Supplies a set of applications for indexing or querying sequence data. GEM is composed of six modulable parts including: (i) core libraries; (ii) header files; (ii) standalones executables that permits to create GEM index or to compute a reference’s mappability; (iv) a suite of retriever tools from various inputs; (v) some converters to allows GEM format to be exported or browsed towards other software and ;(vi) additional information to help users in processing.


A combined strategy to identify junction reads from back spliced exons and intron lariats. CIRCexplorer is now only a circular RNA annotating tool, and it parses fusion junction information from mapping results of other aligners. The result of circular RNA annotating is directly dependent on the mapping strategy of aligners. Different aligners may have different circular RNA annotations. CIRCexplorer is now only in charge of giving fusion junctions a correct gene annotation.

HISAT / Hierarchical Indexing for Spliced Alignment of Transcripts

star_border star_border star_border star_border star_border
star star star star star
A fast and sensitive spliced alignment program for mapping RNA-seq reads. In addition to one global FM index that represents a whole genome, HISAT uses a large set of small FM indexes that collectively cover the whole genome (each index represents a genomic region of ~64,000 bp and ~48,000 indexes are needed to cover the human genome). These small indexes (called local indexes) combined with several alignment strategies enable effective alignment of RNA-seq reads, in particular, reads spanning multiple exons. The memory footprint of HISAT is relatively low (~4.3GB for the human genome).


Detects splice junctions from RNA-seq data. SpliceMap does not depend on any existing annotation of gene structures and is capable of finding novel splice junctions with high sensitivity and specificity. It can handle long reads and can exploit paired-read information to improve mapping accuracy. Workflow of standard SpliceMap and outline of junction search based on half-read mapping, it consists of four steps: half-read mapping, seeding selection, junction search and paired-end filtering.


Examines epigenomic and transcriptomic next generation sequencing (NGS) data. Octopus-toolkit can be used for antibody- or enzyme-mediated experiments and studies for the quantification of gene expression. It can accelerate the data mining of public epigenomic and transcriptomic NGS data for basic biomedical research. This tool provides a private and a public mode: one to process the user’s own data, and the other to analyze public NGS data by retrieving raw files from the GEO database.

G-Mo.R-Se / Gene MOdeling using RNA-Seq

A method aimed at using RNA-Seq short reads to build de novo gene models. First, candidate exons are built directly from the positions of the reads mapped on the genome (without any ab initio assembly of the reads), and all the possible splice junctions between those exons are tested against unmapped reads. The testing of junctions is directed by the information available in the RNA-Seq dataset rather than a priori knowledge about the genome. Exons can thus be chained into stranded gene models.

aRNApipe / automated RNA-seq pipeline

Analyzes single-end and stranded or unstranded paired-end RNA-seq data. aRNApipe focuses on high performance computing (HPC) environments and the independent designation of computational resources at each stage allowing optimization of HPC resources. It is highly flexible because its project configuration and management options. This tool can be adapted to changes in the current applications and the addition of new functionalities. It allows users to complete primary RNA-seq analysis.

RASER / Reads Aligner for SNPs and Editing sites of RNA

An accurate read aligner with novel mapping schemes and index tree structure that aims to reduce false positive mappings due to existence of highly similar regions. RASER shows the best mapping accuracy compared to other popular algorithms and highest sensitivity in identifying multiply mapped reads. As a result, RASER displays superb efficacy in unbiased mapping of the alternative alleles of SNPs and in identification of RNA editing sites.

NGS-Trex / NGS TRanscriptome profile EXplorer

Allows user to upload raw sequences and obtain an accurate characterization of the transcriptome profile. NGS-Trex can assess differential expression at both gene and transcript level. It compares the expression profile of different samples. All comparisons are performed using a custom database which is mainly populated with several sources obtained from the NCBI. The tool allows user to discard ambiguously assigned reads or to assign those reads to all competing genes in the case of ambiguities.


Advances the automation and visualization of RNA-seq data analyses results. QuickRNASeq is a pipeline that significantly reduces data analysts’ hands-on time, which results in a substantial decrease in the time and effort needed for the primary analyses of RNA-seq data before proceeding to further downstream analysis and interpretation. It provides a dynamic data sharing and interactive visualization environment for end users and enable non-expert end users to interact easily with the RNA-seq data analyses results.


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.

RNA CoMPASS / RNA Comprehensive Multi-Processor Analysis System for Sequencing

Analyzes exogenous and human sequences from RNAseq data. RNA CoMPASS is a parallel computation pipeline that provides a graphic user interface built from several open-source programs such as Novoalign and SAMMate. The application reads both the unmapped reads for pathogen discovery and the mapped reads for host transcriptome analysis. The program supports files generated from single-end, paired-end, and/or directional sequencing strategies.


Allows splice junction (SJ) detection. TrueSight is a method developed to improve sensitivity and specificity of mapping SJ spanning RNA-seq reads. The software incorporates information from (i) RNA-seq mapping quality and (ii) coding potentials from the reference genome sequences into a unified model that utilizes adaptive training by iterative logistic regression for de novo identification of SJs and filtering out unreliable SJs. It can accelerate the annotation of new genomes and helps to elucidate the origins of complex traits of different species.


Provides very low false positive rates (FDR) in detecting splice junctions. FANSe2splice is a spliced mapping algorithm that first aligns reads to reference transcriptome and genome sequences in an unspliced way. If the alignment fails, it then aligns the reads as a spliced-read: it allows two hotspots for one read. This is particularly useful in case of RNA-seq, where RNA splicing may occur. This software runs at a reasonable speed even on a normal desktop workstation which requires huge amount of RAM.

ST Pipeline

Permits to process and analyze the raw files generated with the Spatial Transcriptomics (ST) method. ST Pipeline enables demultiplexing of spatially-resolved RNA-seq data and robust quality filtering and identification of unique molecules. It is highly customizable with numerous parameter settings. The tool is more robust, efficient and scales better to arrays with higher density. It filters data, aligns it to a genome, annotates it to a reference, demultiplexes by array coordinates and then aggregates by counts that are not duplicates using the Unique Molecular Identifiers.


Processes RNA-Seq data in a more efficient manner with flexible parameters. Read-Split-Run is a computational method for identifying non-canonical, possibly very short, splicing regions. This pipeline takes RNA-Seq data to align the sequences to the genome of user’s choice, splits the aligned reads, re-aligns them, then performs a sequence of filters to output a table of matched reads and the genes they belong to. It could also be easily extended for prediction of spliced regions for other species under any given parameter settings.


Converts the raw fastq files into gene/isoform expression matrix and differentially expressed genes or isoforms. hppRNA is a one-in-all solution composed of four scenarios such as pre-mapping, core-workflow, post-mapping and sequence variation detection. It also turns the identification of fusion genes, single nucleotide polymorphisms (SNP), long noncoding RNAs and circular RNAs. Finally, this pipeline is specifically designed for performing the systematic analysis on a huge set of samples in one go, ideally for the researchers who intend to deploy the pipeline on their local servers.


Processes large numbers of raw RNA-sequencing datasets. PRADA works on paired-end sequencing data and is based on: (1) its mapping to both transcriptomic and genome; or (2) its comprehensive repertoire of output information from the incorporated modules. It enables users to compute multiple analytical metrics. It provides different types of information from raw paired-end RNA-seq data: gene expression levels, quality metrics, detection of unsupervised and supervised fusion transcripts, detection of intragenic fusion variants, homology scores and fusion frame classification.


Computes cDNA-to-Genome alignments. Splign include a high-performance preliminary alignment, a compartment identification based on a formally defined model of adjacent duplicated regions, and a refined sequence alignment. Its ability to deal with various issues complicating the spliced alignment problem makes it a helpful tool in eukaryotic genome annotation processes and alternative splicing studies. Its performance is enough to align the largest currently available pools of cDNA data such as the human expressed sequence tag (EST) set on a moderate-sized computing cluster in a matter of hours.


Provides an open source RNA-seq processing pipeline that can be used to extract knowledge from any study that profiled gene expression using RNA-seq applied to mammalian cells, comparing two conditions. Zika-RNAseq-Pipeline enables the extraction of knowledge from typical RNA-seq studies by generating interactive principal component analysis (PCA) and hierarchical clustering (HC) plots, performing enrichment analyses against over 90 gene set libraries, and obtaining lists of small molecules that are predicted to either mimic or reverse the observed changes in mRNA expression.


Analyzes the structure and functions of active microbial communities using the power of multi-threading computers. MetaTrans is designed to perform two types of RNA-Seq analyses: taxonomic and gene expression. It performs quality-control assessment, rRNA removal, maps reads against functional databases and also handles differential gene expression analysis. Its efficacy was validated by analyzing data from synthetic mock communities, data from a previous study and data generated from twelve human fecal samples.


An algorithm, quasi-mapping, for mapping sequencing reads to a transcriptome. By attempting only to report the potential loci of origin of a sequencing read, and not the base-to-base alignment by which it derives from the reference, RapMap is capable of mapping sequencing reads to a target transcriptome substantially faster than existing alignment tools. The quasi-mapping algorithm itself uses several efficient data structures and takes advantage of the special structure of shared sequence prevalent in transcriptomes to rapidly provide highly-accurate mapping information.