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T-REx:用于RNA测序表达数据的转录组分析网络服务器。

T-REx: Transcriptome analysis webserver for RNA-seq Expression data.

作者信息

de Jong Anne, van der Meulen Sjoerd, Kuipers Oscar P, Kok Jan

机构信息

Molecular Genetics, University of Groningen, Nijenborgh 7, 9747AG, Groningen, The Netherlands.

Top Institute Food and Nutrition (TIFN), Nieuwe Kanaal 9A, 6709, PA, Wageningen, The Netherlands.

出版信息

BMC Genomics. 2015 Sep 3;16(1):663. doi: 10.1186/s12864-015-1834-4.

Abstract

BACKGROUND

Transcriptomics analyses of bacteria (and other organisms) provide global as well as detailed information on gene expression levels and, consequently, on other processes in the cell. RNA sequencing (RNA-seq) has over the past few years become the most accurate method for global transcriptome measurements and for the identification of novel RNAs. This development has been accompanied by advances in the bioinformatics methods, tools and software packages that deal with the analysis of the large data sets resulting from RNA-seq efforts.

RESULTS

Based on years of experience in analyzing transcriptome data, we developed a user-friendly webserver that performs the statistical analysis on the gene expression values generated by RNA-seq. It also provides the user with a whole range of data plots. We benchmarked our RNA-seq pipeline, T-REx, using a case study of CodY mutants of Bacillus subtilis and show that it could easily and automatically reproduce the statistical analysis of the cognate publication. Furthermore, by mining the correlation matrices, k-means clusters and heatmaps generated by T-REx we observed interesting gene-behavior and identified sub-groups in the CodY regulon.

CONCLUSION

T-REx is a parameter-free statistical analysis pipeline for RNA-seq gene expression data that is dedicated for use by biologists and bioinformaticians alike. The tables and figures produced by T-REx are in most cases sufficient to accurately mine the statistical results. In addition to the stand-alone version, we offer a user-friendly webserver that only needs basic input ( http://genome2d.molgenrug.nl ).

摘要

背景

对细菌(及其他生物体)进行转录组学分析可提供有关基因表达水平以及细胞内其他过程的全面且详细的信息。在过去几年中,RNA测序(RNA-seq)已成为用于全局转录组测量和鉴定新型RNA的最准确方法。这一发展伴随着生物信息学方法、工具和软件包的进步,这些方法、工具和软件包用于分析RNA-seq产生的大量数据集。

结果

基于多年分析转录组数据的经验,我们开发了一个用户友好的网络服务器,它对RNA-seq生成的基因表达值进行统计分析。它还为用户提供一系列数据图。我们以枯草芽孢杆菌的CodY突变体为例对我们的RNA-seq流程T-REx进行了基准测试,结果表明它可以轻松自动地重现相关文献的统计分析。此外,通过挖掘T-REx生成的相关矩阵、k均值聚类和热图,我们观察到有趣的基因行为,并在CodY调控子中识别出亚组。

结论

T-REx是一个用于RNA-seq基因表达数据的无参数统计分析流程,供生物学家和生物信息学家使用。T-REx生成的表格和图形在大多数情况下足以准确挖掘统计结果。除了独立版本外,我们还提供一个用户友好的网络服务器,只需要基本输入(http://genome2d.molgenrug.nl)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d977/4558784/1109f2f7c50f/12864_2015_1834_Fig1_HTML.jpg

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