3D RNA-seq: a powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists.
3D RNA-seq: a powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists.
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DOI：
10.1080/15476286.2020.1858253
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发表时间：
2021-11
期刊：
影响因子：
4.1
通讯作者：
Zhang R
中科院分区：
文献类型：
--
作者：
Guo W;Tzioutziou NA;Stephen G;Milne I;Calixto CP;Waugh R;Brown JWS;Zhang R
基因表达和选择性剪接的RNA测序（RNA-seq）分析应该是常规和稳健的，但由于不同和复杂的分析程序以及对专业生物信息学技能的依赖，这往往是生物学家的瓶颈。我们已经开发了“3D RNA-seq”应用程序，这是一个R shiny应用程序和基于网络的管道，用于全面分析来自任何生物体的RNA-seq数据。它代表了一个易于使用，灵活和强大的工具，用于分析基因和转录水平的基因表达，以确定差异基因/转录表达，差异可变剪接和差异转录使用（3D）以及从RNA-seq数据的异构体转换。3D RNA-seq集成了最先进的差异表达分析工具，并采用了RNA-seq分析的最佳实践。该程序旨在由具有最少生物信息学经验的生物学家（或生物信息学家）运行，允许实验室科学家分析他们的RNA-seq数据。它通过一个用户友好的图形界面来实现这一点，该界面通过管道中的程序自动化数据流。通过3D RNA-seq进行的综合分析非常快速和准确，可以处理复杂的实验设计，允许用户设置统计参数，通过图形和表格可视化结果，并生成出版质量图，如热图，表达谱和GO富集图。3D RNA-seq的效用说明了从一个时间序列的冷处理的拟南芥植物和地塞米松处理的雄性和雌性小鼠皮质和下丘脑数据识别地塞米松诱导的性别和大脑区域特异性差异基因表达和选择性剪接的数据分析。
RNA-sequencing (RNA-seq) analysis of gene expression and alternative splicing should be routine and robust but is often a bottleneck for biologists because of different and complex analysis programs and reliance on specialized bioinformatics skills. We have developed the ‘3D RNA-seq’ App, an R shiny App and web-based pipeline for the comprehensive analysis of RNA-seq data from any organism. It represents an easy-to-use, flexible and powerful tool for analysis of both gene and transcript-level gene expression to identify differential gene/transcript expression, differential alternative splicing and differential transcript usage (3D) as well as isoform switching from RNA-seq data. 3D RNA-seq integrates state-of-the-art differential expression analysis tools and adopts best practice for RNA-seq analysis. The program is designed to be run by biologists with minimal bioinformatics experience (or by bioinformaticians) allowing lab scientists to analyse their RNA-seq data. It achieves this by operating through a user-friendly graphical interface which automates the data flow through the programs in the pipeline. The comprehensive analysis performed by 3D RNA-seq is extremely rapid and accurate, can handle complex experimental designs, allows user setting of statistical parameters, visualizes the results through graphics and tables, and generates publication quality figures such as heat-maps, expression profiles and GO enrichment plots. The utility of 3D RNA-seq is illustrated by analysis of data from a time-series of cold-treated Arabidopsis plants and from dexamethasone-treated male and female mouse cortex and hypothalamus data identifying dexamethasone-induced sex- and brain region-specific differential gene expression and alternative splicing.
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DOI：
10.1093/bioinformatics/btx411
发表时间：
2017-10-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Guo W;Calixto CPG;Brown JWS;Zhang R
通讯作者：
Zhang R
影响因子：
4.6
作者：
Blair, Emily J.;Bonnot, Titouan;Nagel, Dawn H.
通讯作者：
Nagel, Dawn H.
影响因子：
14.9
作者：
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通讯作者：
Smyth GK
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y
影响因子：
14.9
作者：
Liu R;Holik AZ;Su S;Jansz N;Chen K;Leong HS;Blewitt ME;Asselin-Labat ML;Smyth GK;Ritchie ME
通讯作者：
Ritchie ME