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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.
HISAT / Hierarchical Indexing for Spliced Alignment of Transcripts
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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).
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.
STAR / Spliced Transcripts Alignment to a Reference
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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.
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.
RSEM / RNA-Seq by Expectation-Maximization
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Performs gene and isoform level quantification from RNA-Seq data. RSEM is a software package that quantifies gene and isoform abundances from single-end (SE) or paired-end (PE) RNA-Seq data. The software enables visualization of its output through probabilistically-weighted read alignments and read depth plots. It does not require a reference genome and thus can be useful for quantification with de novo transcriptome assemblies.
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.
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.
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.
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.
GESS / Graph-based Exon-Skipping Scanner
Detects de novo exon-skipping events directly from raw RNA-seq data without prior knowledge of gene-annotation information. First, we build a splicing-site-linking graph from splicing-aware aligned reads using a greedy algorithm. We then iteratively scan this linking graph to obtain those patterns conforming to skipping events. Finally, we apply the MISO model to calculate the ratio of skipping versus inclusion isoforms and determine which is the dominant isoform.
RAMICS / Rapid Amplicon Mapping in Codon Space
A hidden Markov model reference mapper, designed to align coding and non-coding DNA to a reference sequence. By default, RAMICS assumes DNA is coding and Sanger-sequenced. Options allow the user to specify the sequencing platform used for more accurate alignment. RAMICS can also be set to training mode, where it will iteratively refine the profile hidden Markov model associated with the reference sequence to the profile of the query sequences aligned to it.
Maps and aligns a single sequence with minimal startup time and memory requirements, and provides fast batch processing of large sequence sets. GMAP is a standalone program for mapping and aligning cDNA sequences to a genome. It generates accurate gene structures, even in the presence of substantial polymorphisms and sequence errors, without using probabilistic splice site models. GMAP can produce alignments in a variety of formats, including a compressed format that saves considerable space.
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.
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.
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.
Allows users simultaneously perform mRNA and miRNA expression analysis. wapRNA is a web application that includes major processes for the next-generation mRNA or miRNA data analysis, including preprocessing raw sequenced reads, mapping tags to reference sequences, gene expression annotation, and other downstream functional analysis such as detecting differentially expressed genes, Gene Ontology and KEGG pathway analysis for RNA, novel miRNA predication and miRNA target prediction. Executable packages are available for users to build their pipeline locally.
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.
Oqtans / Online quantitative transcriptome analysis
Provides a Galaxy interface to RNA-seq analysis tools. Oqtans is the online platform for quantitative RNA-seq data analysis. Its integration into the Galaxy framework ensures transparent and reproducible computational analyses. This application is available in five incarnations: (i) as a cloud machine image, (ii) as a public Galaxy instance, (iii) as a git repository, (iv) the Galaxy Toolshed, and (v) a preconfigured share string to launch Galaxy CloudMan using sharing instance functionality.
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.
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.
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Uses as a splice-aware aligner for short and long reads. BBMap is shown to be a fast and accurate aligner, capable of correctly handling an overall wider variety of references, reads, and mutations than others. It has particularly outstanding performance with deletions, especially long ones, that other aligners cannot handle at all. It can output many different statistics files, such as an empirical read quality histogram, insert-size distribution, and genome coverage, with or without generating a sam file.
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.
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.
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