Unlock your biological data

Try: RNA sequencing CRISPR Genomic databases DESeq

Software Databases Users

1 - 50 of 60 results

1 - 50 of 60 results

GEPIA / Gene Expression Profiling Interactive Analysis

Enables to perform a diverse range of gene expression analyses. GEPIA is an interactive web application which analyzes the RNA sequencing expression data of 9,736 tumors and 8,587 normal samples from the TCGA and the GTEx projects. It provides customizable functions such as tumor/normal differential expression analysis, profiling according to cancer types or pathological stages, patient survival analysis, similar gene detection, correlation analysis and dimensionality reduction analysis.

A Galaxy based web server for processing and visualizing deeply sequenced data. The web server's core functionality consists of a suite of newly developed tools, called deepTools, that enable users with little bioinformatic background to explore the results of their sequencing experiments in a standardized setting. Users can upload pre-processed files with continuous data in standard formats and generate heatmaps and summary plots in a straight-forward, yet highly customizable manner.

A tool for visualizing RNA-seq analysis results. CummeRbund takes the various output files from a cuffdiff run and creates a SQLite database of the results describing appropriate relationships betweeen genes, transcripts, transcription start sites, and CDS regions. Once stored and indexed, data for these features, even across multiple samples or conditions, can be retrieved very efficiently and allows the user to explore subfeatures of individual genes, or genesets as the analysis requires.

Automatically manages the RNA-sequencing pipeline based on the TopHat, Cufflinks and CummeRbund suite of software. Tuxedo allows to assess alternative splicing (AS) inferred on fragments per kilobase per million (FPKM) values.

Allows visualization of microarray data. TreeView is an open source, cross-platform which offers several views, including dendrogram, scatterplot, karyoscope and alignment, with visual cues to show which genes are selected. The software provides fine control over the appearance of dendrogram.

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.

Bundles a series of sophisticated analysis methods with intuitive visualization options to study high-dimensional data with the special focus on gene-centered expression data. It is designed for a broad user community ranging from bioinformaticians with demands for comprehensive analyses in a sophisticated workflow to application-oriented experimenters with needs in intuitive visualization options for their data. The oposSOM package requires the input of gene-centered expression data solely, e.g. as pre-processed microarray intensity data or RNA-seq read counts in log-scale.

Evaluates the performance of RNA-seq measurements in terms of specificity and sensitivity. Rnaseqcomp is a package that offers several quantitative and visualized benchmarks for RNA-seq quantification pipelines. Two-condition quantifications for genes, transcripts, junctions or exons by each pipeline with necessary meta information should be organized into numeric matrices in order to proceed the evaluation.

A software package consisting of a default back end, which prepares raw sequencing or Affymetrix microarray data, and a web-based front end, which offers a biologically centered interface to browse, visualize, and compare different data sets. ExpressionPlot offers the gene expression community an easy-to-use tool for automated analysis of gene expression and RNA processing data. The back end offers a solution to the problem of detecting significant changes in gene expression and RNA processing, while the web-based interface offers data analysis, visualization and browsing tools that realize the biological potential of this new technology.

Allows users to store, visualize and analyze epigenomics and transcriptomics data using a biologist-friendly web interface, without the need for programming expertise. Predefined pipelines allow users to download data, visualize results on a genome browser, calculate RPKMs (reads per kilobase per million) and identify peaks. Advanced capabilities include differential gene expression and binding analysis, and creation of average tag -density profiles and heatmaps.

MeV / Multiple experiment Viewer

Allows to analyse, visualise and stratify large genomic data. MeV is a cloud-based application that gives access to genomic analysis tools, large public domain data sets, intuitive user interfaces, data visualization, and tools for reproducible research. The software allows user to explore the large public data sets, develop and test hypotheses and extend those explorations to their own data. It was designed for use in a variety of different scenarios.

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.

Allows data preparation, analysis and exploration of transcriptome data with t-SNE (t-statistic Stochastic Neighbor Embedding). Visgenex performs better than commonly used methods, offering insight into underlying patterns of gene expression at both global and local scales and identifying clusters of similarly expressed genes. This method can, therefore, be used in conjunction with conventional clustering methods to provide a means to visualize clusters in the context of the entire data set.

Tests significance of clustering in RNA-seq data. SigFuge allows to identify genomic loci exhibiting differential transcription patterns across many RNA-seq samples. It combines clustering with hypothesis testing to identify genes exhibiting alternative splicing, or differences in isoform expression. SigFuge is presented as a method capable of unsupervised discovery of differential isoform events in RNA-seq. This approach of studying gene expression as per-base expression curves along transcriptome coordinates makes it possible to identify differential events without strictly constraining the analysis to proposed exon or transcript boundaries.

MiSTIC / Minimum Spanning Trees Inferred Clustering

Visualizes and compares collections of gene expression profiles, instantly highlighting differences and similarities in gene clustering between cancer types or subtypes. MiSTIC should facilitate identification of new prognostic markers and accelerate improvements in the molecular classification of cancers. Its integrative concept greatly improves the accessibility of complex datasets by end-users and enables the generation of hypotheses on mechanisms driving correlated gene expression. It is adaptable to the analysis of any collection of quantitative profiles.

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.

Calculates a filtering threshold for replicated RNA sequencing data. HTSFilter provides an intuitive data-driven way to filter RNA-seq data and to effectively remove genes with low constant expression levels. HTSFilter may be useful in a variety of applications for RNA-seq data, including differential expression analyses, clustering and co-expression analyses, and network inference.

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.

A package for deconvolution of heterogeneous tissues based on mRNA-Seq data. DeconRNASeq adopts a globally optimized non-negative decomposition algorithm through quadratic programming for estimating the mixing proportions of distinctive tissue types in next-generation sequencing data. It encapsulates the method in a convenient-to-use format. The independent profile-generating module in DeconRNASeq grants freedom to users, who can combine with other R or Bioconductor packages to perform upstream and downstream analysis of NGS data.

A package with quality assessment, processing and visualization tools for high-throughput sequencing data, with emphasis in ChIP-seq and RNA-seq studies. htSeqTools includes detection of outliers and biases, inefficient immuno-precipitation and overamplification artifacts, de novo identification of read-rich genomic regions and visualization of the location and coverage of genomic region lists. htSeqTools can be a valuable complement for pipelines and advanced analysis strategies.

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.

GE-mini / Gene Explorer

Provides a method for displaying expression profiles of all available tumor and tissue types, while allowing drilling down to detailed views for specific tissue types. Users can investigate genes of interest anywhere by using a smart phone, inspecting an expression body map and exploring the tumor-normal differential expression for a wide arrange of tissue types. GE-mini fills in the gap between cancer genomics big data and the delivery of integrated information to end users.

Produces interactive graphics. Glimma aims to enable effective interactive exploration of data from differential expression (DE) analyses. It returns multi-dimensional scaling (MDS) plot that is an unsupervised clustering technique based on the eigenvalue decomposition of euclidean distances between samples based on their gene expression profiles. This tool can be useful to connect summary-level data with sample-level observations and other annotations.

START App / Shiny Transcriptome Analysis Resource Tool App

Provides researchers with increased flexibility to easily upload and visualize RNAseq data. START App visualizes data in multiple ways that will be useful for scientist 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.

VOE / Visual Omics Explorer

A cross-platform data visualization portal that is implemented using only HTML and JavaScript code. VOE is a standalone software that can be loaded offline on the web browser from a local copy of the code, or over the internet without any dependency other than distributing the code through a file sharing service. VOE can interactively display genomics, transcriptomics, epigenomics and metagenomics data stored either locally or retrieved from cloud storage services, and runs on both desktop computers and mobile devices.

A web application for the visualization of strand-specific tiling microarray or next-generation sequencing data that allows customized detection of differentially expressed regions all along the genome in an unspecific manner, that allows identification of all RNA sequences, predictable or not.

anexVis / analysis of RNA expression

Analyzes tissue-specific expression patterns of glycosaminoglycan (GAG) genes. AnexVis facilitates the exploration of RNA expression data of multiple genes across multiple tissue types by integrating different data types and views and presenting them in a highly interactive manner. This application is fully customizable to include other genes and thus, can be useful in many other biological fields. It was implemented as a web application for maximizing accessibility to biological researchers.

Measures replicability by modelling the effects of noise within observed co-expression. AuPairWise employs a noise model to perturb a sample in input expression data. It estimates how it affects the co-expression of gene pairs that are known to be coexpressed. This tool provides a direct quality control measure. It was applied to a microarray data set version of BrainSpan. AuPairWise hinges on an expectation that a particular subset of genes will show correlated expression.

DEIVA / Differential Gene Expression Interactive Visual Analysis

Enables locating and identifying single or multiple genes in an immediate, interactive, and intuitive manner. DEIVA offers a unique combination of design decisions that enable inspection and analysis of differential gene expression (DGE) statistical test results with an emphasis on ease of use. DEIVA is available for local use or as a web application to interactively identify and locate genes in a hexbin or scatter plot of DESeq2 or edgeR results.

Enables users to interrogate and visualize complex transcription profiling data. Datgan allows users to examine the molecular pathogenesis of glaucoma and to view any set of microarray or RNA-seq based transcription profiling datasets. It can be useful for complex diseases that have variable onset and progression. It is designed to permit additional datasets to be easily incorporated after the initial online environment has been constructed.

A workflow system for laboratories with the need to analyze data from multiple NGS projects at a time. QuickNGS takes advantage of parallel computing resources, a comprehensive back-end database, and a careful selection of previously published algorithmic approaches to build fully automated data analysis workflows. QuickNGS considerably reduces the barriers that still limit the usability of the powerful NGS technology and finally decreases the time to be spent before proceeding to further downstream analysis and interpretation of the data.

Allows displaying and explores next generation sequencing (NGS) datasets in a rapid and intuitive way by permitting multiple data attributes to be shown simultaneously. Cascade can analyze RNA-seq data, or whole-exome or genome sequencing (WES/WGS). It employs a variety of tunable parameters to highlight specific attributes of genes/features that are of interest to the researcher. This tool allows researchers and clinicians to make transition from data exploration to hypothesis generation.

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.

iCanPlot / Interactive HTML5 Canvas Plotting Library

A compelling platform for visual data exploration based on the latest technologies. iCanPlot is a highly interactive tool to visualize tabular data and identify interesting patterns in an intuitive fashion without the need of any specialized computing skills. A module for geneset overlap analysis has been implemented on the Google App Engine platform: when the user selects a region of interest in the plot, the genes in the region are analyzed on the fly. The visualization and analysis are amalgamated for a seamless experience. Further, users can easily upload their data for analysis—which also makes it simple to share the analysis with collaborators.

A generalized framework to systematically investigate the synergistic and antagonistic effects of differential splicing and differential expression. dSpliceType detects and prioritizes a list of genes that are differentially expressed and/or spliced. In particular, the multivariate dSpliceType is among the fist to utilize sequential dependency of normalized base-wise read coverage signals and capture biological variability among replicates using a multivariate statistical model.

Allows users to visualize human genome information as well as the next generation sequencing (NGS) sequence data information. RNA-Seq viewer is a mobile application available only with iOS environment. It permits researchers to study and interrogate miRNA-Seq data and can be used for displaying multiple gene expression data (mRNA and miRNA).

Provides a visual framework for analysis of sequencing datasets. VisRseq is a computationally rich and accessible framework for integrative and interactive analyses without requiring programming expertise. VisRseq provides R apps, which offer a semi-auto generated and unified graphical user interface (GUI) for computational packages in R and repositories such as Bioconductor. To address the interactivity limitation inherent in R libraries, this framework includes several native apps that provide exploration and brushing operations as well as an integrated genome browser. The apps can be chained together to create more powerful analysis workflows.

Enables the broad adoption of next generation sequencing (NGS) based inquiries. dictyExpress is a web application designed for exploration of transcriptomics datasets. It allows users to select among experiments and specify genes to analyze; visualize the expression time courses of those genes; identify gene clusters; examine pre-processed differential expression datasets; and perform Gene Ontology (GO)-term enrichment analysis.

Zika-RNAseq-Pipeline

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.

An integrated collection of Perl modules focused on building efficient pipelines for NGS data processing. ViennaNGS comes with functionality for extracting and converting features from common NGS file formats, computation and evaluation of read mapping statistics, as well as normalization of RNA abundance. Moreover, ViennaNGS provides software components for identification and characterization of splice junctions from RNA-seq data, parsing and condensing sequence motif data, automated construction of Assembly and Track Hubs for the UCSC genome browser, as well as wrapper routines for a set of commonly used NGS command line tools.

A tool to identify, annotate and visualise splicing switch events from RNA-seq data. By relying on transcript level quantifications, SwitchSeq provides a simple (yet powerful) approach to identify, annotate and visualise the most extreme changes in splicing across two different conditions, namely switch events.

TRAPR / Total RNA-Seq Analysis Package for R

Facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization. It allows users to build customized analysis pipelines. The tool can be easily applied to other technologies like Serial Analysis of Gene Expression and microarray thanks to its implementation in R.

Allows to analyze the results concerning differential gene expression. VolcanoR takes a table which contains gene name p-value and foldChange as input data. It shows relation between fold change and statistical confidence. It is able to apply different p-value and fold change thresholds and get visualization and gene set over-representation analysis using Gene Ontology (GO) and KEGG databases.

TBro / Transcriptome Browser

Aggregates sequences, their annotation, expression levels as well as differential testing results. TBro provides an easy-to-use interface to mine the aggregated data and generate publication-ready visualizations. Additionally, it supports users with an intuitive cart system, that helps collecting and analysing biological meaningful sets of transcripts. TBro is a fully featured yet flexible transcriptome browser that supports approaching complex biological questions and enhances collaboration of numerous researchers.

ViDGER / Visualization of Differential Gene Expression Results using R

Constructs publication-quality visualizations from Cuffdiff, edgeR, and DESeq2. ViDGER is able to build six different types of expression-based visualizations-boxplots, scatterplots, differentially expressed gene (DEG) counts, MA plots, volcano plots, and Four-way plots. It aims to assist researchers in the interpretation of differential gene expression (DGE) results and to share the result of DGE studies in a graphical manner.

Provides the premier enterprise solution for data content, framework and graphical user interface for omic and next-generation sequencing data analysis. Array Suite (Array Studio and Array Server) differs from standard desktop solutions or open source solutions, with Array Studio providing the graphical user interface for NGS and omic analysis and visualization and Array Server providing the enterprise back-end solution for project management, sample management and data storage.

A web tool to help you analyse, visualize and fully appreciate your differential gene expression data from RNA-seq experiments. Degust consists of a backend that uses limma and edgeR to perform the statistical analysis, and a dynamic frontend for the interactive visualisation.

Qlucore Omics Explorer

Assists users in investigating normalized omics large datasets. Qlucore Omics Explorer is a modular platform divided into four main functionalities (i) Visualization includes features for generating various plots types including principal component analysis (PCA) plots and real-time visualization; (ii) Exploration furnishes tools for comparing, browsing and selecting targeted information (iii) Analysis includes statistical methods such as quadratic regression, f-tests, or ANOVA and (iv) Sharing allows users to export results as multiple formats including videos or variable lists.

Allows exploration of single-cell next-gene sequencing data. SeqGeq permits the discovery of sub-populations, differentially expressed genes and allows the creation of publishable figures with an easy-to-use interface. It can serve to identify population’s relationships as well as examine and construct gene sets.

Facilitates downstream analysis of RNA-seq and similar expression data. ShinyNGS provides Shiny applications for various array and Next-Generation Sequencing (NGS) applications. The software allows selection of gene sets by name or annotation to modify the plots and tables shown, provides progressive filters for differential analysis, large variety of visualizations, UpSet-style intersection plots and gene set enrichment barcode plots.

1
2

0 - 0 of 0 results

1 - 10 of 10 results

1 - 10 of 10 results

Master Korea Advanced Institute of Science and Technology

ToppGene Suite SAMtools Trim Galore!

PhD Student Institute of Life Sciences, Bhubaneswar

Working on Immunology and Systems Biology.

EuMicrobedbLite edgeR FASTX-Toolkit

PhD, CONICET Researcher School of Medical Sciences - UNLP

BioPlat UCSC Xena ClueGO

Antoine Rousselin

Ingénieur d'étude Centre François Baclesse

STAR CNVkit CNV-seq

Computational Biology Pfizer, Inc.

QuickRNASeq

GEPIA GeneCodis

cell biology gibh

SCDE Glbase deepTools

Doc Shanghai Jiaotong University

SPAdes Rockhopper

Gyan Prakash Mishra

Computational Biologist Institute of Life Sciences

Complex heatmaps deepTools

Graduate Research Assistant South Dakota State University

Gene expression visualization software tools | RNA sequencing data analysis

RNA-seq and other forms of gene expression profiling such as CAGE are widely used for measuring RNA abundance profiles of various primary cells and cell lines. By comparing the transcript abundance between two states, genes with statistically significant differences in expression levels can be identified. In addition to large-scale, landscape-type analysis of such differentially expressed genes, often leading to long lists of Gene Ontology terms, it is often desired to perform an interactive visual analysis of the results, focusing on comparatively few genes of interest, heavily dependent on the problem domain.

Source text:
(Harshbarger., 2017) DEIVA: a web application for interactive visual analysis of differential gene expression profiles. BMC Genomics.

Parent categories

Metatranscriptomic sequencing analysis RNA-seq analysis

Related steps

By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.