OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data
1
Department of Molecular, Cell and Cancer Biology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605, USA
2
Program in Molecular Medicine, Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
*
Author to whom correspondence should be addressed.
†
Contributed equally to this work.
Genes 2020, 11(10), 1165; https://doi.org/10.3390/genes11101165
Received: 22 August 2020
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Revised: 22 September 2020
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Accepted: 29 September 2020
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Published: 2 October 2020
(This article belongs to the Special Issue Selected Papers From the Advanced Genetics Conference 2019)
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.
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Keywords:
RNA-seq; workflow; pipeline; web application; quality control; visualization; differential gene expression; alternative-splicing analysis; allele–specific expression quantification; differential transposable element expression analysis; differential exon usage; GSEA
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MDPI and ACS Style
Li, R.; Hu, K.; Liu, H.; Green, M.R.; Zhu, L.J. OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data. Genes 2020, 11, 1165. https://doi.org/10.3390/genes11101165
AMA Style
Li R, Hu K, Liu H, Green MR, Zhu LJ. OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data. Genes. 2020; 11(10):1165. https://doi.org/10.3390/genes11101165
Chicago/Turabian StyleLi, Rui, Kai Hu, Haibo Liu, Michael R. Green, and Lihua Julie Zhu. 2020. "OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data" Genes 11, no. 10: 1165. https://doi.org/10.3390/genes11101165
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