Kapeel M. Chougule, Liya Wang, Joshua C. Stein, Xiaofei Wang, Upendra Kumar Devisetty, Robert R. Klein, Doreen Ware
下载PDF
{"title":"Improved RNA-seq Workflows Using CyVerse Cyberinfrastructure","authors":"Kapeel M. Chougule, Liya Wang, Joshua C. Stein, Xiaofei Wang, Upendra Kumar Devisetty, Robert R. Klein, Doreen Ware","doi":"10.1002/cpbi.53","DOIUrl":null,"url":null,"abstract":"<p>RNA-seq is a vital method for understanding gene structure and expression patterns. Typical RNA-seq analysis protocols use sequencing reads of length 50 to 150 nucleotides for alignment to the reference genome and assembly of transcripts. The resultant transcripts are quantified and used for differential expression and visualization. Existing tools and protocols for RNA-seq are vast and diverse; given their differences in performance, it is critical to select an analysis protocol that is scalable, accurate, and easy to use. Tuxedo, a popular alignment-based protocol for RNA-seq analysis, has been updated with HISAT2, StringTie, StringTie-merge, and Ballgown, and the updated protocol outperforms its predecessor. Similarly, new pseudo-alignment-based protocols like Kallisto and Sleuth reduce runtime and improve performance. However, these tools are challenging for researchers lacking command-line experience. Here, we describe two new RNA-seq analysis protocols, in which all tools are deployed on CyVerse Cyberinfrastructure with user-friendly graphical user interfaces, and validate their performance using plant RNA-seq data. © 2018 by John Wiley & Sons, Inc.</p>","PeriodicalId":10958,"journal":{"name":"Current protocols in bioinformatics","volume":"63 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cpbi.53","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current protocols in bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpbi.53","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 3
引用
批量引用
Abstract
RNA-seq is a vital method for understanding gene structure and expression patterns. Typical RNA-seq analysis protocols use sequencing reads of length 50 to 150 nucleotides for alignment to the reference genome and assembly of transcripts. The resultant transcripts are quantified and used for differential expression and visualization. Existing tools and protocols for RNA-seq are vast and diverse; given their differences in performance, it is critical to select an analysis protocol that is scalable, accurate, and easy to use. Tuxedo, a popular alignment-based protocol for RNA-seq analysis, has been updated with HISAT2, StringTie, StringTie-merge, and Ballgown, and the updated protocol outperforms its predecessor. Similarly, new pseudo-alignment-based protocols like Kallisto and Sleuth reduce runtime and improve performance. However, these tools are challenging for researchers lacking command-line experience. Here, we describe two new RNA-seq analysis protocols, in which all tools are deployed on CyVerse Cyberinfrastructure with user-friendly graphical user interfaces, and validate their performance using plant RNA-seq data. © 2018 by John Wiley & Sons, Inc.
使用CyVerse网络基础设施改进RNA-seq工作流程
RNA-seq是了解基因结构和表达模式的重要方法。典型的RNA-seq分析方案使用长度为50至150个核苷酸的测序reads与参考基因组对齐并组装转录本。结果转录本被量化并用于差异表达和可视化。现有的RNA-seq工具和协议种类繁多;考虑到它们在性能上的差异,选择一个可扩展、准确且易于使用的分析协议是至关重要的。Tuxedo是一种流行的基于比对的RNA-seq分析协议,它已经更新了HISAT2、StringTie、StringTie-merge和Ballgown,更新后的协议优于其前身。类似地,新的基于伪对齐的协议(如Kallisto和Sleuth)减少了运行时间并提高了性能。然而,这些工具对于缺乏命令行经验的研究人员来说是具有挑战性的。在这里,我们描述了两种新的RNA-seq分析协议,其中所有工具都部署在CyVerse网络基础设施上,具有用户友好的图形用户界面,并使用植物RNA-seq数据验证其性能。©2018 by John Wiley &儿子,Inc。
本文章由计算机程序翻译,如有差异,请以英文原文为准。