UMMS Affiliation
Department of Molecular, Cell and Cancer Biology
Publication Date
2020-10-02
Document Type
Article
Disciplines
Bioinformatics | Computational Biology | Databases and Information Systems | Genomics | Health Information Technology | Nucleic Acids, Nucleotides, and Nucleosides
Abstract
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.
Keywords
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
Rights and Permissions
© 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 (http://creativecommons.org/licenses/by/4.0/).
DOI of Published Version
10.3390/genes11101165
Source
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
Journal/Book/Conference Title
Genes
Related Resources
PubMed ID
33023248
Repository Citation
Li R, Hu K, Liu H, Green MR, Zhu LJ. (2020). OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data. Open Access Publications by UMMS Authors. https://doi.org/10.3390/genes11101165. Retrieved from https://escholarship.umassmed.edu/oapubs/4410
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Included in
Bioinformatics Commons, Computational Biology Commons, Databases and Information Systems Commons, Genomics Commons, Health Information Technology Commons, Nucleic Acids, Nucleotides, and Nucleosides Commons