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Department of Molecular, Cell and Cancer Biology

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Bioinformatics | Computational Biology | Databases and Information Systems | Genomics | Health Information Technology | Nucleic Acids, Nucleotides, and Nucleosides


Over the past decade, a large amount of RNA sequencing (RNA-seq) data were deposited in public repositories, and more are being produced at an unprecedented rate. However, there are few open source tools with point-and-click interfaces that are versatile and offer streamlined comprehensive analysis of RNA-seq datasets. To maximize the capitalization of these vast public resources and facilitate the analysis of RNA-seq data by biologists, we developed a web application called OneStopRNAseq for the one-stop analysis of RNA-seq data. OneStopRNAseq has user-friendly interfaces and offers workflows for common types of RNA-seq data analyses, such as comprehensive data-quality control, differential analysis of gene expression, exon usage, alternative splicing, transposable element expression, allele-specific gene expression quantification, and gene set enrichment analysis. Users only need to select the desired analyses and genome build, and provide a Gene Expression Omnibus (GEO) accession number or Dropbox links to sequence files, alignment files, gene-expression-count tables, or rank files with the corresponding metadata. Our pipeline facilitates the comprehensive and efficient analysis of private and public RNA-seq data.


GSEA, RNA-seq, allele–specific expression quantification, alternative-splicing analysis, differential exon usage, differential gene expression, differential transposable element expression analysis, pipeline, quality control, visualization, web application, workflow

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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (

DOI of Published Version



Li R, Hu K, Liu H, Green MR, Zhu LJ. OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data. Genes (Basel). 2020 Oct 2;11(10):1165. doi: 10.3390/genes11101165. PMID: 33023248; PMCID: PMC7650687. Link to article on publisher's site

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Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.