Offers a way to manage pipelines. Toil supports arbitrary worker and leader failure, with strong check-pointing that allows resumption. It can be employed to run scientific workflows on a large scale in cloud or high-performance computing (HPC) environments. This tool was used to compute gene- and isoform- level expression values for 19 952 samples from four studies.
Offers a platform for population-level analyses. dDocent is an open-source software dedicated to individually barcoded restriction-site associated DNA sequencing (RADseq) data processing. The application employs data reduction techniques and interact with other programs to propose features such as de novo assembly of RAD loci, single nucleotides polymorphisms (SNPs) and indel calling as well as quality trimming or baseline data filtering.
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.
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).
A cloud computing tool for calculating differential gene expression in large RNA-seq datasets. Myrna uses Bowtie for short read alignment and R/Bioconductor for interval calculations, normalization, and statistical testing. These tools are combined in an automatic, parallel pipeline that runs in the cloud (Elastic MapReduce in this case) on a local Hadoop cluster, or on a single computer, exploiting multiple computers and CPUs wherever possible.
Provides a workflow for RNA-Seq-based differential gene expression (DGE) analysis. RobiNA gathers multiple packages and software with the aim of furnishing a cross-platform processing in four main steps: (i) quality assessment and filtering; (ii) mapping the reads to a user-provided reference genome or transcriptome; (iii) perform the experimental design and (iv) statistical analysis of DGE.
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.
Identifies differentially expressed genes from count data or previously normalized count data. NOISeq empirically models the noise distribution of count changes by contrasting fold-change differences (M) and absolute expression differences (D) for all the features in samples within the same condition. This reference distribution is then used to assess whether the M-D values computed between two conditions for a given gene are likely to be part of the noise or represent a true differential expression.
Establishes a central, redistributable workbench for scientists and programmers working with RNA-related data. The RNA workbench builds a sustainable community around it. This platform is unique in combining available tools, workflows and training material, as well as providing easy access for experimentalists. It serves as a central hub for programmers, which can easily integrate and deploy their existing or novel tools and workflows.
A powerful analysis tool of genome-wide mRNA-seq or ChIP-seq data for detecting differentially expressed genes or identifying changes in epigenetic modifications (histone acetylation/methylation patterns). EpiCenter is also capable of performing genome-wide TFBS peaking detection and generating read coverage depth plot data (e.g., WIG files for UCSC genome browser).
A graphical user interface that helps biologists to handle and analyse large data collected in RNA-seq experiments. The novel version of RNASeqGUI combines graphical interfaces with tools for reproducible research, such as literate statistical programming, human readable report, parallel executions, caching, and interactive and web-explorable tables of results. These features allow the user to analyse big datasets in a fast, efficient, and reproducible way.
Aims to reduce the efforts put into basic data processing for next-generation sequencing (NGS). QuickNGS enables data analysis for major applications of NGS in a batch-like operation mode. This pipeline relies on the organization of available metadata in a MySQL database which is used to control the overall workflow composed of specific software applications for different kinds of analysis.
Assists users in manipulating high-throughput sequencing (HTS) data and formats. Picard is a Java toolkit that provides a set of command line scripts. It comprises Java-based utilities that manipulate SAM files, and a Java API for creating new programs that reads and writes SAM files. Both SAM text format and SAM binary (BAM) format are supported. It also works with next generation sequencing (NGS).
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.
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.
Serves for processing RNA-Seq data. easyRNASeq is a program that combines the necessary packages in a single wrapper that ensures the pertinence of the provided data and information. It also assists users to circumnavigate RNA-Seq processing pitfalls. Moreover, it introduces functionalities to handle data produced by recent next-generation sequencing (NGS) protocols.
Assists in analyzing RNA-Seq data. RSEQtools contains a set of modules to perform a large variety of tasks including: (i) the quantification of expression values, (ii) the manipulation of gene annotation sets, (iii) the visualization of the mapped reads, (iv) the generation of signal tracks, (v) the identification of transcriptional active regions and several auxiliary utilities.
Provides an integrated analysis of high-throughput sequencing data in R, covering all steps from read preprocessing, alignment and quality control to quantification. QuasR supports different experiment types (including RNA-seq, ChIP-seq and Bis-seq) and analysis variants (e.g. paired-end, stranded, spliced and allele-specific), and is integrated in Bioconductor so that its output can be directly processed for statistical analysis and visualization.
Aims to ease high-throughput sequencing (HTS) data analysis by the using of distributed computation. Eoulsan is a framework able to perform its tasks on distributed computers. The application includes batch analyses, a full automation process managing external file locations and distributed file system. It can be run according three modes: standalone, local cluster or cloud computing on Amazon Elastic MapReduce.
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.
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.
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.
Facilitates analysis of microarrays and miRNA/RNA-seq data on laptops. oneChannelGUI can be used for quality control, normalization, filtering, statistical validation and data mining for single channel microarrays. It consists of a didactical tool that can be employed to introduce scientists to the utilization and interpretation of microarray data. This tool serves in the investigation of microarray experiments based on the consolidated 3’ Affymetrix expression arrays.
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.
Analyses mapped reads from diverse High-throughput sequencing (HTS) experiments: ChIP-Seq, either punctuated or broad signals, CLIP-Seq and RNA-Seq. Pyicos is a command line utility for the conversion and manipulation of genomic coordinates files. It facilitates HTS analysis through its flexibility and memory efficiency, providing a useful framework for data integration into models of regulatory genomics. Pyicos is part of the Pyicoteo suite of tools.
Permits the computational evaluation of RNA-Seq data. READemption is an automated RNA-Seq processing with the initial purpose to handle differential RNA-Seq (dRNA-Seq) data for the determination of transcriptional start sites (TSSs) from bacterial, archaeal and eukaryotic species as well as for RNA virus genomes. READemption generates several output files that can be examined with common office suites, graphic programs and genome browser.
Allows analysis of millions of short reads obtained from high-throughput RNA-Seq experiments. Grape is a workflow that automates the steps from RNA-Seq reads to transcript quantification and discovery. Its objective is to produce quantifications of transcript abundances and of the abundances of other transcriptional elements such as genes, exons, or splice junctions. It can be directly used to produce quantifications if an index from a reference transcriptome-independently assembled is generated.
Allows users to characterize and quantify the set of all RNA molecules produced in cells. RseqFlow contains several modules that include: mapping reads to genome and transcriptome references, performing quality control (QC) of sequencing data, generating files for visualizing signal tracks based on the mapping results, calculating gene expression levels, identifying differentially expressed genes, calling coding single nucleotide polymorphisms (SNPs) and producing MRF and BAM files.
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.
Allows to develop tailored workflows for the analysis of whole-exome (WES), whole-genome (WGS), and transcriptome (RNA-seq) sequencing data. NGS-pipe is an automated framework for the design of pipelines for the analysis of large-scale sequencing data, such as cancer genomics data. It provides building blocks to execute state-of-the-art tools, as well as appropriate error handling. It also overcome the common lack of automated procedures to ensure reproducibility.
Performs RNA-seq data analysis through the Elastic Compute Cloud (EC2) service. NGSCloud is a platform allowing users to: (i) generate, view composition, and manipulate clusters and its associated nodes; (ii) manage volumes; (iii) handle datasets with various utilities for compressing or uploading; (iv) manage jobs and check for program operability in an RNA-seq workflow. This program focuses on non-model species with no reference genomes available.
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 raw reads to count tables for RNA-seq data using Unique Molecular Identifiers (UMIs). zUMIs is a pipeline applicable for most experimental designs of RNA-seq data, such as single-nuclei sequencing techniques. This method allows for down sampling of reads before summarizing UMIs per feature, which is recommended for cases of highly different read numbers per sample. zUMIs is flexible with respect to the length and sequences of the barcodes (BCs) and UMIs, making it compatible with a large number of protocols.
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.
Serves for the characterization of long noncoding RNA molecules (lncRNA) from raw transcriptome sequencing data. LncPipe is a Nextflow-based computational pipeline for systematical identification and analyses of lncRNAs from RNA-seq data. This software contains four main analysis procedures including read alignment, lncRNA identification, sequence assembly and differential expression analysis. It provides various features such as pipeline canceling, parameters resetting and analysis resuming from any continuous checkpoint.
Designed for mRNA, miRNA and circRNA identification and differential expression analysis, applicable to any sequenced organism. miARma-Seq is presented as a stand-alone tool that provides different well-established softwares at ease of installation process. It can analyse a large number of samples due to its multithread design. During the whole analysis miARma-Seq performs several quality control analysis creating quality reports for an easy evaluation of the data.
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.
Consists of a collection of investigation approaches and displays software for microarray data. Chipster is useful for several types of high throughput data such as microarrays, proteomics and next generation sequencing (NGS). It can be employed to normalize most of the commonly used chip types and permits to utilize the remapped information. This tool is useful for RNA degradation, relative log expression (RLE), normalized unscaled standard error (NUSE) or quality control probe expression.
Integrates data from different sources and experiments. CANEapp is a platform for integrating next-generation sequencing (NGS) analysis pipelines and tools into a user-friendly suite that can be immediately accessed by scientists. It utilizes a standardized analysis pipeline and internally generated experimental design templates. It allows users to work on NGS data and high-throughput data.
Allows users to analyze sequencing data in multiple steps. The RAP purpose is to investigate the complex transcriptional landscape of eukaryotic transcriptomes through a computationally optimized RNA-Seq data analysis. Users can perform a complete RNA-Seq analysis without any specific technical competence. It offers a web interface and provides different types of results which consist of several tabular and graphical representations.
Includes three types of workflows for different tasks. RNA-seq portal permits users to perform computing and analysis, including sequence quality control, read-mapping, transcriptome assembly, reconstruction and differential analysis. All these workflows support multiple samples and multiples groups of samples and perform differential analysis between groups in a single workflow job submission. This web portal offers bioinformatics software, workflows, computation and reference data and a platform to study complex RNA-seq data analysis for agricultural animal species.
Performs the analysis of sequencing data from cross-linking, ligation and sequencing of hybrids (CLASH) experiments. hyb is able to recognize chimeric reads in other applications as well as for the analysis of UV cross-linking and analysis of cDNAs (CRAC), crosslinking and immunoprecipitation (CLIP), and RNA-Seq data. This tool can be useful and applicable to any next-generation sequencing datasets.
Processes pathway and clustering analysis of time series RNA-seq data. TRAP exploits over-representation analysis (ORA) and signaling pathway impact analysis (SPIA) methods to evaluate pathways interactions between genes. Time points, i.e., time series are analyzed by the software to estimate a single pathway-level statistic. It enables multiple thresholds and customized pathways made of genes of interest for analyzing data.
Assembles large-scale expressed sequence tags (EST) datasets and automatically identifies and correct assembly errors. iAssembler employs an iterative assembly strategy and automated assembly error corrections to deliver highly accurate de novo assemblies of EST sequences. This method contains seven major functional modules: (i) general controller, (ii) MIRA assembler, (iii) CAP3 assembler, (iv) megablast assembler, (v) type I error corrector, (vi) type II error corrector, and (vii) unigene base corrector.
A fully automated RNA-Seq based report for patients with (breast) cancer, which includes molecular classification, detection of altered genes, detection of altered pathways, identification of gene fusion events, identification of clinical actionable mutations (in coding regions) and identification of treatable target structures. Furthermore, OncoRep reports suitable drugs based on identified actionable targets, which can be considered in the treatment decision making process.
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.
Serves for methodical analysis for both single and comparative transcriptome data. TCW contains two manager programs: (1) singleTCW for building a database of annotated sequences with differential expression (DE) results for a single species; and (2) multiTCW for building a database of multiple species with comparison results. This approach can be used for the large-scale processing and online databases to extract information.
A multi-level bioinformatics protocol and pipeline. RNAMiner includes five steps: Mapping RNA-Seq reads to a reference genome, calculating gene expression values, identifying differentially expressed genes, predicting gene functions, and constructing gene regulatory networks.
Provides a platform for storing, handling and processing next generation sequencing (NGS) data. OTP performs both data management and processing and allows users to automate an entire process to raw data import from storage. The application includes functionalities for check quality control and sequence alignment and identify single-nucleotide and structural genomic events.
Assists users in obtaining genomic features from transcriptomic sequencing data, for any genome. MAP-RSeq is a comprehensive computational workflow, to align, assess and report multiple genomic features from paired-end RNA-Seq data. It uses a variety of freely available bioinformatics tools along with in-house developed methods using Perl, Python, R, and Java. This application is available in two versions: (i) a single threaded that runs on a virtual machine (VM) and (ii) a multi-threaded designed to run on a cluster environment.