Li, RuiHu, KaiLiu, HaiboGreen, Michael R.Zhu, Lihua Julie2022-08-232022-08-232020-10-022020-12-03<p>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. <a href="https://doi.org/10.3390/genes11101165">Link to article on publisher's site</a></p>2073-4425 (Linking)10.3390/genes1110116533023248https://hdl.handle.net/20.500.14038/41621Over 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.en-US© 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/).http://creativecommons.org/licenses/by/4.0/GSEARNA-seqallele–specific expression quantificationalternative-splicing analysisdifferential exon usagedifferential gene expressiondifferential transposable element expression analysispipelinequality controlvisualizationweb applicationworkflowBioinformaticsComputational BiologyDatabases and Information SystemsGenomicsHealth Information TechnologyNucleic Acids, Nucleotides, and NucleosidesJournal Articlehttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=5440&amp;context=oapubs&amp;unstamped=1https://escholarship.umassmed.edu/oapubs/441020386594oapubs/4410