S/N Software Platform Link (URL) Description Reference
1 Python, R UTAP  https://utap.readthedocs.io UTAP (User-friendly Transcriptome Analysis Pipeline) is an open source, web-based intuitive and scalable transcriptome pipeline that executes the full process, starting from sequences (RNA-Seq and bulk MARS-Seq), ending with sets of differentially expressed genes and sophisticated reports, and requiring minimal user expertise. Kohen et al., 2019
2 Python RASflow https://github.com/zhxiaokang/RASflow. RASflow (RNA-Seq Analysis Snakemake Workflow) is a lightweight and easy-to-manage RNA-Seq analysis workflow. It includes the complete workflow for RNA-Seq analysis, starting with QC of the raw FASTQ files, going through optional trimming, alignment and feature counting (if the reads are mapped to a genome), pseudo alignment (if transcriptome is used as mapping reference), gene- or transcript- level DEA, and visualization of the output from DEA. Zhang and Jonassen, 2020.
3 R ARMOR ARMOR (Automated Reproducible MOdular RNA-Seq) is a Snakemake workflow, aimed at performing a typical RNA-seq workflow in a reproducible, automated, and partially contained manner. It is implemented such that alternative or similar analysis can be added or removed. Orjuela et al., 2019
4 R, Python, Unix, C++, java, Perl VIPER  https://bitbucket.org/cfce/viper/ VIPER (Visualization Pipeline for RNA-Seq) is a comprehensive RNA-Seq analysis tool built using snakemake which allows for ease of use, optimal speed, and a highly modular code that can be further added onto and customized by experienced users. VIPER combines the use of several dozen RNA-Seq tools, suites, and packages to create a complete pipeline that takes RNA-Seq analysis from raw sequencing data all the way through alignment, quality control, unsupervised analysis, differential expression, and downstream pathway analysis. Cornwell et al., 2018
5 web Biojupies http://biojupies.cloud. BioJupies is a web application that enables the automated creation, storage, and deployment of Jupyter Notebooks containing RNA-Seq data analyses. Through an intuitive interface, novice users can rapidly generate tailored reports to analyse and visualize their own raw sequencing files, gene expression tables, or fetch data from >9,000 published studies containing >300,000 pre-processed RNA-Seq samples. Torre et al., 2018.
6 Perl, R hppRNA https://sourceforge.net/projects/hpprna/. hppRNA package is dedicated to the RNA-Seq analysis for a large number of samples simultaneously from the very beginning to the very end, which is formulated in Snakemake pipeline management system. It starts from fastq files and will produce gene/isoform expression matrix, differentially-expressed-genes, sample clusters as well as detection of SNP and fusion genes by combination of the state-of-the-art software. Wang, 2018
7 Python RNA Cocktail http://bioinform.github.io/rnacocktail/. The RNACocktail pipeline is composed of high-accuracy tools for different steps of RNA-Seq analysis. It performs a broad-spectrum RNA-Seq analysis on both short- and long-read technologies to enable meaningful insights from transcriptomic data. It was developed after analysing a variety of RNA-Seq samples (ranging from germline, cancer to stem cell datasets) and technologies using a multitude of tool combinations to determine a pipeline which is comprehensive, fast and accurate Sahraeian et al., 2017
8 Python aRNApipe https://github.com/HudsonAlpha/aRNAPipe aRNApipe is a project-oriented pipeline for processing of RNA-seq data in high performance cluster environments. The provided framework is highly modular and has been designed to be deployed on HPC environments using IBM Platform LSF, although it can be easily migrated to any other workload manager. Alonso et al., 2017
9 Python, R UTAP https://utap.readthedocs.io BISR-RNAseq (Bioinformatics Shared Resource Group-RNAseq) is a consistent workflow that allows for the analysis (alignment, QC, gene-wise counts generation) of raw RNAseq data and seamless integration of quality analysis and differential expression results into a configurable R shiny web application. Kohen et al., 2019
10 Python, R, Shell RASflow https://github.com/zhxiaokang/RASflow TRAPLINE (Transparent, Reproducible and Automated PipeLINE) supports NGS-based research by providing a workflow that requires no bioinformatics skills, decreases the processing time of the analysis, and works in the cloud Zhang and Jonassen, 2020
11 Python, R & Bash BISR-RNAseq https://github.com/MPiet11/BISR-RNAseq The docker4seq package was developed to facilitate the use of computing demanding applications in the field of NGS data analysis. It uses docker containers that embed demanding computing tasks (e.g., short reads mapping) into isolated containers. Gadepalli et al., 2019
12 web TRAPLINE https://usegalaxy.org/u/mwolfien/p/trapline—manual QuickRNASeq is an open-source based pipeline for large scale RNA-Seq data analysis. It takes advantage of parallel computing resources, a careful selection of previously published algorithms for RNA-Seq read mapping, counting and quality control, and a three-stage strategy to build a fully automated workflow. Wolfien et al., 2016
13 R Docker4seq http://reproducible-bioinformatics.org IRIS-EDA (Interactive RNA-Seq Interpretation System for Expression Data Analysis) provides a user-friendly interactive platform to analyse gene expression data comprehensively and to generate interactive summary visualizations readily. In contrast to other analysis platforms, IRIS-EDA provides the user with a more comprehensive and multi-level analysis platform. Kulkarn et al., 2018.
14 Bash scripting, Perl, R, JavaScript QuickRNAseq http://quickrnaseq.sourceforge.net bcbioRNASeq is a Bioconductor package that provides ready-to-render templates, objects and wrapper functions to post-process bcbio RNA sequencing output data. It helps automate the generation of high-level RNA-Seq reports, facilitating the quality control analyses, identification of differentially expressed genes and functional enrichment analyses. He et al., 2018
15 web IRIS-EDA  http://bmbl.sdstate.edu/IRIS/. START (Shiny Transcriptome Analysis Resource Tool) provides researchers with increased flexibility to easily upload and visualize RNA-Seq data. The App visualizes data in multiple ways that will be useful for scientists to understand their data. Critical to facilitating data sharing capabilities, the App can be utilized within a web browser environment for easy access as well as enabling seamless sharing of data between collaborators. Monier et al., 2019
16 R bcbioRNASeq https://github.com/hbc/bcbioRNASeq iDEP (integrated Differential Expression and Pathway analysis) enables users to conduct in-depth bioinformatics analysis of transcriptomic data through a GUI. The two use cases demonstrated that it can help pinpoint molecular pathways from large genomic datasets, thus eliminating some barriers for modern biologists. Steinbaugh et al., 2018
17 R START https://kcvi.shinyapps.io/START DEApp (Differential Expression App) interactive and dynamic web application for differential expression analysis of count based NGS data. It enables models selection, parameter tuning, cross validation and visualization of results in a user-friendly interface. Nelson et al., 2017
18 R iDEP http://ge-lab.org/idep/ GENAVi (Gene Expression Normalization Analysis and Visualization) provides a user-friendly interface for normalization and differential expression analysis (DEA) of human or mouse feature count level RNA-Seq data. It is a GUI based tool that combines Bioconductor packages in a format for scientists without bioinformatics expertise. Ge et al., 2018
19 R DEApp https://yanli.shinyapps.io/DEApp TCC-GUI (Graphical User Interface for TCC) is a browser-based application for DE analysis of RNA-Seq data. It enables non-R users to perform the TCC package without installation. In addition to the functionalities originally implemented in TCC, TCC-GUI provides plenty of interactive visualization functions. The powerful in-built functions would also be satisfactory for experienced R users. Li and Andrade, 2017
20
R
GENAVi
https://junkdnalab.shinyapps.io/GENAVi/
BEAVR (Browser-based tool for the Exploration and Visualization of RNA-Seq data) is an easy-to-use tool that facilitates interactive analysis and exploration of RNA-Seq data. It is developed in R and uses DESeq2 as its engine for differential gene expression (DGE) analysis, but assumes users have no prior knowledge of R or DESeq2. BEAVR allows researchers to easily obtain a table of differentially expressed genes with statistical testing and then visualize the results in a series of graphs, plots and heatmaps.
Rayes et al., 2019
21 Web, R TCC-GUI https://infinityloop.shinyapps.io/TCC-GUI/ iSeq, an R-based Web server, for RNA-Seq data analysis and visualization. iSeq is a streamlined Web-based R application under the Shiny framework, featuring a simple user interface and multiple data analysis modules. Users without programming and statistical skills can analyse their RNA-Seq data and construct publication-level graphs through a standardized yet customizable analytical pipeline. Su et al., 2019
22 R BEAVR https://github.com/developerpiru/BEAVR and https://hub.docker.com/r/pirunthan/beavr DaMiRseq package is a structured and convenient workflow to effectively identify transcriptional biomarkers and exploit them for classification purposes. Perampalam and Dick,2020
23 R iSeq http://iseq.cbi.pku.edu.cn. DEsubs is a network-based systems biology R package that extracts disease-perturbed sub pathways within a pathway network as recorded by RNA-Seq experiments. It contains an extensive and customized framework with a broad range of operation modes at all stages of the sub pathway analysis, enabling a case-specific approach. Zhang et al., 2018
24 R DaMiRseq https://bioconductor.org/packages/DaMiRseq/ CANEapp (Comprehensive automated Analysis of Next-generation sequencing Experiments App) is a unique suite that combines a Graphical User Interface (GUI) and an automated server-side analysis pipeline that is platform-independent, making it suitable for any server architecture. Chiesa et al., 2018
25 R DEsubs http://bioconductor.org/packages/DEsubs/. DiCoExpress is an R script-based tool allowing users to perform a full RNA-Seq analysis from quality controls to co-expression analysis through differential analysis based on contrasts inside generalized linear models. DiCoExpress focuses on the statistical modelling of gene expression according to the experimental design and facilitates the data analysis leading the biological interpretation of the results. Vrahatis et al., 2016
26 Python, Java CANEapp http://psychiatry.med.miami.edu/research/laboratory-of-translational-rna-genomics/CANE-app IRIS-DGE (Integrated RNA-Seq Data Analysis and Interpretation System for Differential Gene Expression) is a server-based DGE analysis tool developed using Shiny. It provides a straightforward, user-friendly platform for performing comprehensive DGE analysis, and crucial analyses that help design hypotheses and to determine key genomic features Velmeshev et al., 2016
27 R DicoExpress  https://forgemia.inra.fr/GNet/dicoexpress SPARTA (Simple Program for Automated reference-based bacterial RNA-Seq Transcriptome Analysis) is a reference-based bacterial RNA-Seq analysis workflow application for single-end Illumina reads. SPARTA is turnkey software that simplifies the process of analysing RNA-Seq data sets, making bacterial RNA-Seq analysis a routine process that can be undertaken on a personal computer or in the classroom. Lambert et al., 2020.
28 R IRIS-DGE http://bmbl.sdstate.edu/IRIS/ RAP (RNA-Seq Analysis Pipeline) is a web application implementing a fully automated analysis workflow, designed to integrate in-house developed scripts as well as open-source analysis tools into one pipeline. Monier et al., 2018.
29 Python SPARTA http://sparta.readthedocs.org Shiny-Seq provides a guided and easy to use comprehensive RNA-Seq data analysis pipeline. It has many features such as batch effect estimation and removal, quality check with several visualization options, enrichment analysis with multiple biological databases, identification of patterns using advanced methods such as weighted gene co-expression network analysis, summarizing analysis as PowerPoint presentation and all results as tables via a one-click feature Johnson et al., 2016
30 web RAP  http://bioinformatics.cineca.it/rap/. The Cancer Genome Atlas (TCGA) is a large-scale study that has catalogued genomic data accumulated for many different types of cancers, and includes mutations, copy number variation, mRNA and miRNA gene expression, and DNA methylation. Being publicly distributed, it has become a major resource for cancer researchers in target discovery and in the biological interpretation and assessment of the clinical impact of genes of interest. D’Antonio et al., 2015
31 R Shiny-seq  https://szenitha.shinyapps.io/shiny-seq3/ A multitude of large-scale studies, e.g., TCGA and GTEx, have recently generated an unprecedented volume of RNA-Seq data. The RNA-Seq expression data from different studies typically are not directly comparable, due to differences in sample and data processing and other batch effects. Here, we developed a pipeline that processes and unifies RNA-Seq data from different studies. Using the pipeline, we have processed data from the GTEx and TCGA and have successfully corrected for study-specific biases, allowing comparative analysis across studies. Sundararajan et al., 2019
32 R TCGA RNA seq https://github.com/srp33/TCGA_RNASeq_Clinical. The Toil RNA-Seq workflow converts RNA sequencing data into gene- and transcript-level expression quantification. Mumtahena et al., 2015
33 R RNAseqDB https://github.com/mskcc/RNAseqDB/ BioJupies is a web application that enables the automated creation, storage, and deployment of Jupyter Notebooks containing RNA-Seq data analyses. Through an intuitive interface, novice users can rapidly generate tailored reports to analyse and visualize their own raw sequencing files, gene expression tables, or fetch data from >9,000 published studies containing >300,000 pre-processed RNA-Seq samples. Wang et al., 2018
34 python ToilRNA seq https://github.com/BD2KGenomics/toil-rnaseq hppRNA package is dedicated to the RNA-Seq analysis for a large number of samples simultaneously from the very beginning to the very end, which is formulated in Snakemake pipeline management system. It starts from fastq files and will produce gene/isoform expression matrix, differentially-expressed-genes, sample clusters as well as detection of SNP and fusion genes by combination of the state-of-the-art software. Vivian et al., 2017