Dai Yilin, Guo Ling, Li Meng, Chen Yi-Bu
Department of Mathematical Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49934, USA.
BMC Res Notes. 2012 Jun 8;5:282. doi: 10.1186/1756-0500-5-282.
Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results.
We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs.
Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.
对于那些因不了解R语言而无法使用强大的Bioconductor及其众多工具的研究人员来说,微阵列数据分析是一项重大挑战。在现有的少数几个为Bioconductor软件包提供图形用户界面的软件程序中,由于许多广泛使用的微阵列芯片存在众所周知的探针设计问题,没有一个实施全面的策略来解决微阵列数据分析的准确性和可靠性问题。此外,也缺乏能够加快微阵列结果功能分析的工具。
我们展示了Microarray Я US,这是一个基于R的图形用户界面,它实现了十几个流行的Bioconductor软件包,为研究人员提供了一个简化的工作流程,用于常规差异微阵列表达数据分析,而无需学习R语言。为了能够更准确地分析和解释微阵列数据,我们纳入了针对Affymetrix和Illumina芯片的最新自定义探针重新定义和重新注释。还实现了一个通用的微阵列结果输出实用工具,以便轻松快速地为20多种最广泛使用的功能分析软件程序生成输入文件。
结合精心设计的用户界面,Microarray Я US为不了解R语言的研究人员利用了前沿的Bioconductor软件包。它还能实现更可靠、准确的微阵列数据分析,并加快微阵列结果的下游功能分析。