RAGER: A user-friendly computational platform for integrated analysis of RNA-Seq and ATAC-seq data.

Abstract

Technical advances in RNA sequencing (RNA-seq) and Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) provide us a genome-wide method to deeper insights into gene expression and regulation. The lack of user-friendly bioinformatics platforms poses a challenge for accurately interpreting such datasets. Here, we present a computational platform, RAGER, that integrates the popular bioinformatics tools in an automated thread for joint mining of RNA-seq and ATAC-seq data. RAGER facilitates integrative analysis of transcriptome and chromatin accessibility by providing an automated workflow that minimizes the need for bioinformatics expertise and significantly reduces processing time. We demonstrate RAGER's utility for novel biological discovery by characterizing the transcriptome and chromatin accessibility of two recently published datasets. RAGER was implemented using Snakemake and is freely available via https://github.com/bioinfo202408/RAGER.