RNASequest: An End-to-End Reproducible RNAseq Data Analysis and Publishing Framework

J Mol Biol. 2023 Jul 15;435(14):168017. doi: 10.1016/j.jmb.2023.168017. Epub 2023 Feb 16.

Abstract

We present RNASequest, a customizable RNA sequencing (RNAseq) analysis, app management, and result publishing framework. Its three-in-one RNAseq data analysis ecosystem consists of (1) a reproducible, configurable expression analysis (EA) module, (2) multi-faceted result presentation in R Shiny, a Bookdown document and an online slide deck, and (3) a centralized data management system. In principle, following up our well-received omics data visualization tool Quickomics, RNASequest automates the differential gene expression analysis step, eases statistical model design by built-in covariates testing module, and further provides a web-based tool, ShinyOne, to manage apps powered by Quickomics and reports generated by running the pipeline on multiple projects in one place. Researchers can experience the functionalities by exploring demo data sets hosted at http://shinyone.bxgenomics.com or following the tutorial, https://interactivereport.github.io/RNASequest/tutorial/docs/introduction.html to set up the framework locally to process private RNAseq datasets. The source code released under MIT open-source license is provided at https://github.com/interactivereport/RNASequest.

Keywords: R Shiny; RNAseq; data analysis framework; data management system; web-based software.

MeSH terms

  • RNA-Seq*
  • Sequence Analysis, RNA*
  • Software*