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微分析器:Affymetrix 微阵列数据的自动预处理。

Micro-Analyzer: automatic preprocessing of Affymetrix microarray data.

机构信息

Bioinformatics Laboratory, Department of Surgical and Medical Sciences, Magna Graecia University, Catanzaro, Italy.

出版信息

Comput Methods Programs Biomed. 2013 Aug;111(2):402-9. doi: 10.1016/j.cmpb.2013.04.006. Epub 2013 May 31.

Abstract

A current trend in genomics is the investigation of the cell mechanism using different technologies, in order to explain the relationship among genes, molecular processes and diseases. For instance, the combined use of gene-expression arrays and genomic arrays has been demonstrated as an effective instrument in clinical practice. Consequently, in a single experiment different kind of microarrays may be used, resulting in the production of different types of binary data (images and textual raw data). The analysis of microarray data requires an initial preprocessing phase, that makes raw data suitable for use on existing analysis platforms, such as the TIGR M4 (TM4) Suite. An additional challenge to be faced by emerging data analysis platforms is the ability to treat in a combined way those different microarray formats coupled with clinical data. In fact, resulting integrated data may include both numerical and symbolic data (e.g. gene expression and SNPs regarding molecular data), as well as temporal data (e.g. the response to a drug, time to progression and survival rate), regarding clinical data. Raw data preprocessing is a crucial step in analysis but is often performed in a manual and error prone way using different software tools. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of different microarray data are needed. The paper presents Micro-Analyzer (Microarray Analyzer), a cross-platform tool for the automatic normalization, summarization and annotation of Affymetrix gene expression and SNP binary data. It represents the evolution of the μ-CS tool, extending the preprocessing to SNP arrays that were not allowed in μ-CS. The Micro-Analyzer is provided as a Java standalone tool and enables users to read, preprocess and analyse binary microarray data (gene expression and SNPs) by invoking TM4 platform. It avoids: (i) the manual invocation of external tools (e.g. the Affymetrix Power Tools), (ii) the manual loading of preprocessing libraries, and (iii) the management of intermediate files, such as results and metadata. Micro-Analyzer users can directly manage Affymetrix binary data without worrying about locating and invoking the proper preprocessing tools and chip-specific libraries. Moreover, users of the Micro-Analyzer tool can load the preprocessed data directly into the well-known TM4 platform, extending in such a way also the TM4 capabilities. Consequently, Micro Analyzer offers the following advantages: (i) it reduces possible errors in the preprocessing and further analysis phases, e.g. due to the incorrect choice of parameters or due to the use of old libraries, (ii) it enables the combined and centralized pre-processing of different arrays, (iii) it may enhance the quality of further analysis by storing the workflow, i.e. information about the preprocessing steps, and (iv) finally Micro-Analzyer is freely available as a standalone application at the project web site http://sourceforge.net/projects/microanalyzer/.

摘要

目前基因组学的一个趋势是使用不同的技术来研究细胞机制,以解释基因、分子过程和疾病之间的关系。例如,基因表达阵列和基因组阵列的联合使用已被证明是临床实践中的一种有效工具。因此,在单个实验中可以使用不同类型的微阵列,从而产生不同类型的二进制数据(图像和原始文本数据)。微阵列数据的分析需要进行初始预处理阶段,使原始数据适合于现有分析平台(如 TIGR M4(TM4)套件)使用。新兴数据分析平台面临的另一个挑战是能够以组合方式处理这些不同的微阵列格式以及临床数据。事实上,生成的集成数据可能包括数值和符号数据(例如分子数据中的基因表达和单核苷酸多态性)以及临床数据中的时间数据(例如对药物的反应、进展时间和存活率)。原始数据预处理是分析中的一个关键步骤,但通常使用不同的软件工具以手动且容易出错的方式进行。因此,需要新颖的、与平台无关的、可能是开源的工具,以实现不同微阵列数据的半自动预处理和注释。本文介绍了 Micro-Analyzer(微阵列分析器),这是一种用于 Affymetrix 基因表达和 SNP 二进制数据自动归一化、汇总和注释的跨平台工具。它是 μ-CS 工具的演进,扩展了预处理以包括 μ-CS 不允许的 SNP 阵列。Micro-Analyzer 作为一个 Java 独立工具提供,使用户能够通过调用 TM4 平台来读取、预处理和分析二进制微阵列数据(基因表达和 SNP)。它避免了:(i)手动调用外部工具(例如 Affymetrix Power Tools),(ii)手动加载预处理库,以及(iii)管理中间文件,例如结果和元数据。Micro-Analyzer 用户可以直接管理 Affymetrix 二进制数据,而无需担心定位和调用适当的预处理工具和芯片特定库。此外,Micro-Analyzer 工具的用户可以直接将预处理后的数据加载到著名的 TM4 平台中,从而以这种方式扩展 TM4 的功能。因此,Micro-Analyzer 具有以下优势:(i)它减少了预处理和进一步分析阶段的可能错误,例如由于参数选择不正确或由于使用旧库,(ii)它支持不同阵列的组合和集中预处理,(iii)它可以通过存储工作流程(即预处理步骤的信息)来提高进一步分析的质量,以及(iv)最后,Micro-Analyzer 作为一个独立应用程序免费提供在项目网站 http://sourceforge.net/projects/microanalyzer/ 上。

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