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OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7650687/ https://www.ncbi.nlm.nih.gov/pubmed/33023248 http://dx.doi.org/10.3390/genes11101165 |
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author | Li, Rui Hu, Kai Liu, Haibo Green, Michael R. Zhu, Lihua Julie |
author_facet | Li, Rui Hu, Kai Liu, Haibo Green, Michael R. Zhu, Lihua Julie |
author_sort | Li, Rui |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7650687 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76506872020-11-10 OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data Li, Rui Hu, Kai Liu, Haibo Green, Michael R. Zhu, Lihua Julie Genes (Basel) Article 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. MDPI 2020-10-02 /pmc/articles/PMC7650687/ /pubmed/33023248 http://dx.doi.org/10.3390/genes11101165 Text en © 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/). |
spellingShingle | Article Li, Rui Hu, Kai Liu, Haibo Green, Michael R. Zhu, Lihua Julie OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data |
title | OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data |
title_full | OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data |
title_fullStr | OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data |
title_full_unstemmed | OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data |
title_short | OneStopRNAseq: A Web Application for Comprehensive and Efficient Analyses of RNA-Seq Data |
title_sort | onestoprnaseq: a web application for comprehensive and efficient analyses of rna-seq data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7650687/ https://www.ncbi.nlm.nih.gov/pubmed/33023248 http://dx.doi.org/10.3390/genes11101165 |
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