Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.
Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.
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DOI：
10.1186/1471-2105-10-354
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发表时间：
2009-10-27
影响因子：
3
通讯作者：
Kolisis FN
中科院分区：
文献类型：
--
作者：
Chatziioannou A;Moulos P;Kolisis FN
通过各种工具、开源和商业的发展，微阵列数据分析领域不断发展。然而，缺乏预定义的合理算法分析工作流程或批量标准化处理，以纳入从原始数据导入到推导显着差异表达基因列表的所有步骤。这种缺失混淆了分析过程，阻碍了基因组微阵列数据集的大规模比较处理。此外，所提供的解决方案在很大程度上依赖于用户的编程技能，而在GUI嵌入式解决方案的情况下，它们不提供对各种原始图像分析格式的直接支持，也不提供信号处理方法的通用且同时灵活的组合。我们在这里描述Gene ARMADA（自动鲁棒微阵列数据分析），一个具有图形用户界面的MATLAB实现平台。该套件集成了微阵列数据分析的所有步骤，包括自动数据导入，噪声校正和过滤，归一化，差异表达基因的统计选择，聚类，分类和注释。在其当前版本中，Gene ARMADA完全支持2色cDNA和Affymetrix寡核苷酸阵列，加上自定义阵列，实验细节以表格形式给出（Excel电子表格，逗号分隔值，制表符分隔的文本格式）。它还支持通过其多功能导入编辑器分析已处理的结果。除了完全自动化之外，Gene ARMADA还结合了MATLAB的统计和生物信息学工具箱的许多功能。此外，它还提供了许多可视化和探索工具以及可定制的导出数据格式，以便与其他分析工具或MATLAB进行无缝集成，以进行进一步处理。Gene ARMADA需要MATLAB 7.4 （R2007a）或更高版本，也可以作为带有MATLAB Component Runtime的独立应用程序分发。Gene ARMADA提供了一种高度适应性，集成，灵活的工具，可用于微阵列数据的自动化质量控制，分析，注释和可视化，构成了进一步数据解释和与许多其他工具集成的起点。
The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a highly adaptable, integrative, yet flexible tool which can be used for automated quality control, analysis, annotation and visualization of microarray data, constituting a starting point for further data interpretation and integration with numerous other tools.
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影响因子：
12.3
作者：
Gentleman RC;Carey VJ;Bates DM;Bolstad B;Dettling M;Dudoit S;Ellis B;Gautier L;Ge Y;Gentry J;Hornik K;Hothorn T;Huber W;Iacus S;Irizarry R;Leisch F;Li C;Maechler M;Rossini AJ;Sawitzki G;Smith C;Smyth G;Tierney L;Yang JY;Zhang J
通讯作者：
Zhang J
影响因子：
5.8
作者：
Knowlton, N;Dozmorov, IM;Centola, M
通讯作者：
Centola, M
影响因子：
5.8
作者：
Schultze, Joachim L.;Eggle, Daniela
通讯作者：
Eggle, Daniela
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：
10.5
作者：
Nielsen, Ronni;Pedersen, Thomas Askov;Stunnenberg, Hendrik G.
通讯作者：
Stunnenberg, Hendrik G.