scholarly journals MicroScope: ChIP-seq and RNA-seq software analysis suite for gene expression heatmaps

2015 ◽  
Author(s):  
Bohdan B. Khomtchouk ◽  
James R. Hennessy ◽  
Claes Wahlestedt
Keyword(s):  
Web Application ◽  
Differential Expression Analysis ◽  
Dynamic Network ◽  
Principal Component ◽  
Rna Seq ◽  
Software Suite ◽  
Software Analysis ◽  
Link Type ◽  
R Shiny ◽  
User Friendly

AbstractWe propose a user-friendly ChIP-seq and RNA-seq software suite for the interactive visualization and analysis of genomic data, including integrated features to support differential expression analysis, interactive heatmap production, principal component analysis, gene ontology analysis, and dynamic network analysis.MicroScope is hosted online as an R Shiny web application based on the D3 JavaScript library: http://microscopebioinformatics.org/. The methods are implemented in R, and are available as part of the MicroScope project at: https://github.com/Bohdan-Khomtchouk/Microscope.

scholarly journals GENAVi: a shiny web application for gene expression normalization, analysis and visualization

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Alberto Luiz P. Reyes ◽  
Tiago C. Silva ◽  
Simon G. Coetzee ◽  
Jasmine T. Plummer ◽  
Brian D. Davis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Web Application ◽  
Differential Expression Analysis ◽  
Rna Seq ◽  
Data Analyst ◽  
Reproducible Analysis ◽  
Programming Knowledge ◽  
Next Generation Sequencing Ngs ◽  
User Friendly ◽  
Feature Count

Abstract Background The development of next generation sequencing (NGS) methods led to a rapid rise in the generation of large genomic datasets, but the development of user-friendly tools to analyze and visualize these datasets has not developed at the same pace. This presents a two-fold challenge to biologists; the expertise to select an appropriate data analysis pipeline, and the need for bioinformatics or programming skills to apply this pipeline. The development of graphical user interface (GUI) applications hosted on web-based servers such as Shiny can make complex workflows accessible across operating systems and internet browsers to those without programming knowledge. Results We have developed GENAVi (Gene Expression Normalization Analysis and Visualization) to provide a user-friendly interface for normalization and differential expression analysis (DEA) of human or mouse feature count level RNA-Seq data. GENAVi is a GUI based tool that combines Bioconductor packages in a format for scientists without bioinformatics expertise. We provide a panel of 20 cell lines commonly used for the study of breast and ovarian cancer within GENAVi as a foundation for users to bring their own data to the application. Users can visualize expression across samples, cluster samples based on gene expression or correlation, calculate and plot the results of principal components analysis, perform DEA and gene set enrichment and produce plots for each of these analyses. To allow scalability for large datasets we have provided local install via three methods. We improve on available tools by offering a range of normalization methods and a simple to use interface that provides clear and complete session reporting and for reproducible analysis. Conclusion The development of tools using a GUI makes them practical and accessible to scientists without bioinformatics expertise, or access to a data analyst with relevant skills. While several GUI based tools are currently available for RNA-Seq analysis we improve on these existing tools. This user-friendly application provides a convenient platform for the normalization, analysis and visualization of gene expression data for scientists without bioinformatics expertise.

scholarly journals GREIN: An Interactive Web Platform for Reanalyzing GEO RNA-seq Data

2018 ◽  
Author(s):  
Naim Al Mahi ◽  
Mehdi Fazel Najafabadi ◽  
Marcin Pilarczyk ◽  
Michal Kouril ◽  
Mario Medvedovic
Keyword(s):  
Gene Expression ◽  
User Interfaces ◽  
Web Application ◽  
Statistical Power ◽  
Functional Characterization ◽  
Gene Expression Omnibus ◽  
Rna Seq ◽  
Link Type ◽  
Front End ◽  
User Friendly

ABSTRACTThe vast amount of RNA-seq data deposited in Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA) is still a grossly underutilized resource for biomedical research. To remove technical roadblocks for reusing these data, we have developed a web-application GREIN (GEO RNA-seq Experiments Interactive Navigator) which provides user-friendly interfaces to manipulate and analyze GEO RNA-seq data. GREIN is powered by the back-end computational pipeline for uniform processing of RNA-seq data and the large number (>6,500) of already processed datasets. The front-end user interfaces provide a wealth of user-analytics options including sub-setting and downloading processed data, interactive visualization, statistical power analyses, construction of differential gene expression signatures and their comprehensive functional characterization, and connectivity analysis with LINCS L1000 data. The combination of the massive amount of back-end data and front-end analytics options driven by user-friendly interfaces makes GREIN a unique open-source resource for re-using GEO RNA-seq data. GREIN is accessible at: https://shiny.ilincs.org/grein, the source code at: https://github.com/uc-bd2k/grein, and the Docker container at: https://hub.docker.com/r/ucbd2k/grein.

scholarly journals DEAR-O: Differential Expression Analysis based on RNA-seq data - Online

2016 ◽  
Author(s):  
Zong-Hong Zhang ◽  
Naomi R. Wray ◽  
Qiong-Yi Zhao
Keyword(s):  
Differential Expression ◽  
Expression Analysis ◽  
Online Discussion ◽  
Differential Expression Analysis ◽  
Rna Seq ◽  
Timely Manner ◽  
Link Type ◽  
Online Discussion Forum ◽  
User Friendly ◽  
Transcriptomic Studies

AbstractSummaryDifferential expression analysis using high-throughput RNA sequencing (RNA-seq) data is widely applied in transcriptomic studies and many software tools have been developed for this purpose. Active development of existing popular tools, together with emergence of new tools means that studies comparing the performance of differential expression analysis methods become rapidly out-of-date. In order to enable researchers to evaluate new and updated software in a timely manner, we developed DEAR-O, a user-friendly platform for performance evaluation of differential expression analysis based on RNA-seq data. The platform currently includes four of the most popular tools: DESeq, DESeq2, edgeR and Cuffdiff2. Based on the DEAR-O platform, researchers can evaluate the performance of different tools, or the same tool with different versions, with a customised number of biological replicates using already curated RNA-seq datasets. We also initiated an online forum for discussion of RNA-seq differential expression analysis. Through this forum, new useful tools and benchmarking datasets can be introduced. Our platform will be actively maintained to ensure new major versions of existing tools and new popular tools are included. DEAR-O will serve the community by providing timely evaluations of tools, versions and number of replicates for RNA-seq differential expression analysis.Availability and implementationThe DEAR-O platform is available at http://cnsgenomics.com/software/dear-o; the online discussion forum is https://groups.google.com/d/forum/[email protected] and [email protected]

scholarly journals UBiT2: a client-side web-application for gene expression data analysis

2017 ◽  
Author(s):  
Jean Fan ◽  
David Fan ◽  
Kamil Slowikowski ◽  
Nils Gehlenborg ◽  
Peter Kharchenko
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Single Cell ◽  
Web Application ◽  
Differential Expression Analysis ◽  
Principal Component ◽  
Interactive Visualizations ◽  
Alignment Analysis ◽  
User Friendly ◽  
Client Side

We present a purely client-side web-application, UBiT2 (User-friendly BioInformatics Tools), that provides installation-free, offline alignment, analysis, and visualization of RNA-sequencing as well as qPCR data. Analysis modules were designed with single cell transcriptomic analysis in mind. Using just a browser, users can perform standard analyses such as quality control, filtering, hierarchical clustering, principal component analysis, differential expression analysis, gene set enrichment testing, and more, all with interactive visualizations and exportable publication-quality figures. We apply UBiT2 to recapitulate findings from single cell RNA-seq and Fluidigm Biomark TM multiplex RT-qPCR gene expression datasets. UBiT2 is available at http://pklab.med.harvard.edu/jean/ubit2/index.html with open-source code available at https://github.com/JEFworks/ubit2.

scholarly journals gwaRs: an R shiny web application for visualizing genome-wide association studies data

2020 ◽  
Author(s):  
Lethukuthula L Nkambule
Keyword(s):  
Web Application ◽  
Association Studies ◽  
Principal Component ◽  
Gwas Data ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Web Browser ◽  
Link Type ◽  
Genome Wide ◽  
R Shiny

AbstractSummaryAlthough there is an exponential increase and extensive availability of genome-wide association studies data, the visualization of this data remains difficult for non-specialist users. Current software and packages for visualizing GWAS data are intended for specialists and have been developed to accomplish specific functions, favouring functionality over user experience. To facilitate this, we have developed an R shiny web application, gwaRs, that allows any general user to visualize GWAS data efficiently and effortlessly. The gwaRs web-browser interface allows users to visualize GWAS data using SNP-density, quantile-quantile, Manhattan, and Principal Component Analysis plots.AvailabilityThe gwaRs web application is publicly hosted at https://gwasviz.shinyapps.io/gwaRs/ and R source code is released under the GNU General Public License and freely available at GitHub: https://github.com/LindoNkambule/[email protected]

scholarly journals PathScore: a web tool for identifying altered pathways in cancer data

2016 ◽  
Author(s):  
Stephen G. Gaffney ◽  
Jeffrey P. Townsend
Keyword(s):  
Web Application ◽  
Somatic Mutations ◽  
Supplementary Information ◽  
Web Tool ◽  
Cancer Data ◽  
Link Type ◽  
Novel Approach ◽  
Supplementary Material ◽  
User Friendly ◽  
Pathway Effect

ABSTRACTSummaryPathScore quantifies the level of enrichment of somatic mutations within curated pathways, applying a novel approach that identifies pathways enriched across patients. The application provides several user-friendly, interactive graphic interfaces for data exploration, including tools for comparing pathway effect sizes, significance, gene-set overlap and enrichment differences between projects.Availability and ImplementationWeb application available at pathscore.publichealth.yale.edu. Site implemented in Python and MySQL, with all major browsers supported. Source code available at github.com/sggaffney/pathscore with a GPLv3 [email protected] InformationAdditional documentation can be found at http://pathscore.publichealth.yale.edu/faq.

scholarly journals Mining human cancer datasets for kallikrein expression in cancer: the ‘KLK-CANMAP’ Shiny web tool

2018 ◽  
Vol 399 (9) ◽  
pp. 983-995
Author(s):  
Chenwei Wang ◽  
Leire Moya ◽  
Judith A. Clements ◽  
Colleen C. Nelson ◽  
Jyotsna Batra
Keyword(s):  
Web Application ◽  
Cancer Survival ◽  
Human Cancer ◽  
Web Tool ◽  
Significant Differential Expression ◽  
Box Plots ◽  
Kaplan Meier ◽  
R Shiny ◽  
Serine Protease Family ◽  
User Friendly

AbstractThe dysregulation of the serine-protease family kallikreins (KLKs), comprising 15 genes, has been reportedly associated with cancer. Their expression in several tissues and physiological fluids makes them potential candidates as biomarkers and therapeutic targets. There are several databases available to mine gene expression in cancer, which often include clinical and pathological data. However, these platforms present some limitations when comparing a specific set of genes and can generate considerable unwanted data. Here, several datasets that showed significant differential expression (p<0.01) in cancer vs. normal (n=118), metastasis vs. primary (n=15) and association with cancer survival (n=21) have been compiled in a user-friendly format from two open and/or publicly available databases Oncomine and OncoLnc for the 15 KLKs. The data have been included in a free web application tool: the KLK-CANMAP https://cancerbioinformatics.shinyapps.io/klk-canmap/. This tool integrates, analyses and visualises data and it was developed with the R Shiny framework. Using KLK-CANMAP box-plots, heatmaps and Kaplan-Meier graphs can be generated for the KLKs of interest. We believe this new cancer KLK focused web tool will benefit the KLK community by narrowing the data visualisation to only the genes of interest.

MetENP/MetENPWeb: An R package and web application for metabolomics enrichment and pathway analysis in Metabolomics Workbench

2020 ◽  
Author(s):  
Kumari Sonal Choudhary ◽  
Eoin Fahy ◽  
Kevin Coakley ◽  
Manish Sud ◽  
Mano R Maurya ◽  
...  
Keyword(s):  
Pathway Analysis ◽  
Web Application ◽  
Enrichment Analysis ◽  
R Package ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Kegg Pathways ◽  
Link Type ◽  
Species Specific ◽  
User Friendly

ABSTRACTWith the advent of high throughput mass spectrometric methods, metabolomics has emerged as an essential area of research in biomedicine with the potential to provide deep biological insights into normal and diseased functions in physiology. However, to achieve the potential offered by metabolomics measures, there is a need for biologist-friendly integrative analysis tools that can transform data into mechanisms that relate to phenotypes. Here, we describe MetENP, an R package, and a user-friendly web application deployed at the Metabolomics Workbench site extending the metabolomics enrichment analysis to include species-specific pathway analysis, pathway enrichment scores, gene-enzyme information, and enzymatic activities of the significantly altered metabolites. MetENP provides a highly customizable workflow through various user-specified options and includes support for all metabolite species with available KEGG pathways. MetENPweb is a web application for calculating metabolite and pathway enrichment analysis.Availability and ImplementationThe MetENP package is freely available from Metabolomics Workbench GitHub: (https://github.com/metabolomicsworkbench/MetENP), the web application, is freely available at (https://www.metabolomicsworkbench.org/data/analyze.php)

scholarly journals An open RNA-Seq data analysis pipeline tutorial with an example of reprocessing data from a recent Zika virus study

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 1574 ◽  
Author(s):  
Zichen Wang ◽  
Avi Ma'ayan
Keyword(s):  
Small Molecules ◽  
Zika Virus ◽  
Principal Component ◽  
Global Gene Expression ◽  
Brain Morphology ◽  
Rna Seq ◽  
Link Type ◽  
Neuronal Progenitors ◽  
Global Gene Expression Profiling ◽  
Data Files

RNA-seq analysis is becoming a standard method for global gene expression profiling. However, open and standard pipelines to perform RNA-seq analysis by non-experts remain challenging due to the large size of the raw data files and the hardware requirements for running the alignment step. Here we introduce a reproducible open source RNA-seq pipeline delivered as an IPython notebook and a Docker image. The pipeline uses state-of-the-art tools and can run on various platforms with minimal configuration overhead. The 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. We apply the pipeline to a recently published RNA-seq dataset collected from human neuronal progenitors infected with the Zika virus (ZIKV). In addition to confirming the presence of cell cycle genes among the genes that are downregulated by ZIKV, our analysis uncovers significant overlap with upregulated genes that when knocked out in mice induce defects in brain morphology. This result potentially points to the molecular processes associated with the microcephaly phenotype observed in newborns from pregnant mothers infected with the virus. In addition, our analysis predicts small molecules that can either mimic or reverse the expression changes induced by ZIKV. The IPython notebook and Docker image are freely available at: http://nbviewer.jupyter.org/github/maayanlab/Zika-RNAseq-Pipeline/blob/master/Zika.ipynb and https://hub.docker.com/r/maayanlab/zika/.

scholarly journals BatchServer: a web server for batch effect evaluation, visualization and correction

2020 ◽  
Author(s):  
Tiansheng Zhu ◽  
Guo-Bo Chen ◽  
Chunhui Yuan ◽  
Rui Sun ◽  
Fangfei Zhang ◽  
...  
Keyword(s):  
Web Server ◽  
Batch Effect ◽  
Variance Component Analysis ◽  
Data Sets ◽  
Batch Effects ◽  
Source Codes ◽  
Link Type ◽  
R Shiny ◽  
User Friendly ◽  
Web Platform

AbstractBatch effects are unwanted data variations that may obscure biological signals, leading to bias or errors in subsequent data analyses. Effective evaluation and elimination of batch effects are necessary for omics data analysis. In order to facilitate the evaluation and correction of batch effects, here we present BatchSever, an open-source R/Shiny based user-friendly interactive graphical web platform for batch effects analysis. In BatchServer we introduced autoComBat, a modified version of ComBat, which is the most widely adopted tool for batch effect correction. BatchServer uses PVCA (Principal Variance Component Analysis) and UMAP (Manifold Approximation and Projection) for evaluation and visualizion of batch effects. We demonstate its application in multiple proteomics and transcriptomic data sets. BatchServer is provided at https://lifeinfo.shinyapps.io/batchserver/ as a web server. The source codes are freely available at https://github.com/guomics-lab/batch_server.

Sign in / Sign up

Export Citation Format

Share Document