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RAGER: A user-friendly computational platform for integrated analysis of RNA-Seq and ATAC-seq data
Yunjie Liu1, Yijia Liu2, Zhouming Zhang3
1Jiangxi Provincial Key Laboratory of Tumor Biology, School of Basic Medicine, Jiangxi Medical College, Nanchang University, China.
Plos One
|May 22, 2026
Summary
RAGER is a new bioinformatics platform that integrates RNA sequencing (RNA-seq) and Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) data. This tool simplifies the joint analysis of gene expression and chromatin accessibility, enabling faster biological discovery.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- RNA sequencing (RNA-seq) and ATAC-seq are powerful genome-wide techniques for studying gene expression and regulation.
- Interpreting complex RNA-seq and ATAC-seq datasets requires specialized bioinformatics expertise, posing a significant challenge.
- Existing bioinformatics platforms often lack user-friendliness and integration capabilities for joint analysis.
Purpose of the Study:
- To develop a user-friendly computational platform, RAGER, for the integrated analysis of RNA-seq and ATAC-seq data.
- To automate the joint mining of transcriptome and chromatin accessibility data, reducing the need for extensive bioinformatics knowledge.
- To accelerate biological discovery by simplifying and speeding up the processing of multi-omics sequencing data.
Main Methods:
- RAGER integrates popular bioinformatics tools into an automated workflow using Snakemake.
- The platform facilitates the joint analysis of RNA sequencing (RNA-seq) and Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) data.
- The utility of RAGER was demonstrated by characterizing transcriptome and chromatin accessibility in two published datasets.
Main Results:
- RAGER provides an automated workflow for the integrative analysis of RNA-seq and ATAC-seq data.
- The platform significantly reduces processing time and the requirement for bioinformatics expertise.
- RAGER successfully facilitated the characterization of gene expression and chromatin accessibility in tested datasets, supporting novel biological insights.
Conclusions:
- RAGER is an effective computational platform for the joint analysis of RNA-seq and ATAC-seq data.
- The automated workflow streamlines complex genomic analyses, making them more accessible to researchers.
- RAGER has the potential to accelerate discoveries in gene regulation and molecular biology.
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