Dataset Information

BEAVR: a browser-based tool for the exploration and visualization of RNA-seq data.

ABSTRACT: BACKGROUND:The use of RNA-sequencing (RNA-seq) in molecular biology research and clinical settings has increased significantly over the past decade. Despite its widespread adoption, there is a lack of simple and interactive tools to analyze and explore RNA-seq data. Many established tools require programming or Unix/Bash knowledge to analyze and visualize results. This requirement presents a significant barrier for many researchers to efficiently analyze and present RNA-seq data. RESULTS:Here we present BEAVR, a Browser-based tool for the Exploration And Visualization of RNA-seq data. BEAVR is an easy-to-use tool that facilitates interactive analysis and exploration of RNA-seq data. BEAVR 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. Users are able to customize many parameters for statistical testing, dealing with variance, clustering methods and pathway analysis to generate high quality figures. CONCLUSION:BEAVR simplifies analysis for novice users but also streamlines the RNA-seq analysis process for experts by automating several steps. BEAVR and its documentation can be found on GitHub at https://github.com/developerpiru/BEAVR. BEAVR is available as a Docker container at https://hub.docker.com/r/pirunthan/beavr.

SUBMITTER: Perampalam P

PROVIDER: S-EPMC7260831 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

BEAVR: a browser-based tool for the exploration and visualization of RNA-seq data.

Perampalam Pirunthan P Dick Frederick A FA

BMC bioinformatics 20200529 1

<h4>Background</h4>The use of RNA-sequencing (RNA-seq) in molecular biology research and clinical settings has increased significantly over the past decade. Despite its widespread adoption, there is a lack of simple and interactive tools to analyze and explore RNA-seq data. Many established tools require programming or Unix/Bash knowledge to analyze and visualize results. This requirement presents a significant barrier for many researchers to efficiently analyze and present RNA-seq data.<h4>Resu ...[more]

PMID: 32471392

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Project description:Improvements in next-generation sequencing technologies have resulted in dramatically reduced sequencing costs. This has led to an explosion of '-seq'-based methods, of which RNA sequencing (RNA-seq) for generating transcriptomic data is the most popular. By analysing global patterns of gene expression in organs/tissues/cells of interest or in response to chemical or environmental perturbations, researchers can better understand an organism's biology. Tools designed to work with large RNA-seq data sets enable analyses and visualizations to help generate hypotheses about a gene's function. We present here a user-friendly RNA-seq data exploration tool, called the 'eFP-Seq Browser', that shows the read map coverage of a gene of interest in each of the samples along with 'electronic fluorescent pictographic' (eFP) images that serve as visual representations of expression levels. The tool also summarizes the details of each RNA-seq experiment, providing links to archival databases and publications. It automatically computes the reads per kilobase per million reads mapped expression-level summaries and point biserial correlation scores to sort the samples based on a gene's expression level or by how dissimilar the read map profile is from a gene splice variant, to quickly identify samples with the strongest expression level or where alternative splicing might be occurring. Links to the Integrated Genome Browser desktop visualization tool allow researchers to visualize and explore the details of RNA-seq alignments summarized in eFP-Seq Browser as coverage graphs. We present four cases of use of the eFP-Seq Browser for ABI3, SR34, SR45a and U2AF65B, where we examine expression levels and identify alternative splicing. The URL for the browser is https://bar.utoronto.ca/eFP-Seq_Browser/. OPEN RESEARCH BADGES: This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. Tool is at https://bar.utoronto.ca/eFP-Seq_Browser/; RNA-seq data at https://s3.amazonaws.com/iplant-cdn/iplant/home/araport/rnaseq_bam/ and https://s3.amazonaws.com/iplant-cdn/iplant/home/araport/rnaseq_bam/Klepikova/. Code is available at https://github.com/BioAnalyticResource/eFP-Seq-Browser.

Dataset Information

BEAVR: a browser-based tool for the exploration and visualization of RNA-seq data.

Publications

BEAVR: a browser-based tool for the exploration and visualization of RNA-seq data.

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