EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data.
EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data.
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DOI：
10.1186/1471-2105-10-50
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发表时间：
2009-02-06
影响因子：
3
通讯作者：
Goesmann, Alexander
中科院分区：
文献类型：
--
作者：
Dondrup, Michael;Albaum, Stefan P.;Griebel, Thasso;Henckel, Kolja;Juenemann, Sebastian;Kahlke, Tim;Kleindt, Christiane K.;Kuester, Helge;Linke, Burkhard;Mertens, Dominik;Mittard-Runte, Virginie;Neuweger, Heiko;Runte, Kai J.;Tauch, Andreas;Tille, Felix;Puehler, Alfred;Goesmann, Alexander
通过全基因组微阵列研究了解转录调控有助于揭示基因之间的复杂关系。标准化微阵列数据注释的尝试包括微阵列实验的最低信息 (MIAME) 建议、用于数据交换的 MAGE-ML 格式以及受控词汇或本体的使用。现有的微阵列数据分析软件系统仅部分实现了上述标准，并且通常难以使用和扩展。因此，使用开放标准集成基因组注释数据和其他外部知识源是未来集成分析系统的关键要求。 EMMA 2 软件旨在解决完整 MAGE-ML 和本体支持方面的缺点，并利用现代数据集成技术。我们推出的软件系统具有针对斑点阵列以及最常见的合成寡核苷酸阵列（例如 Agilent、Affymetrix 和 NimbleGen）的全面数据分析功能。该系统基于完整的 MAGE 对象模型。分析功能基于 R 和 Bioconductor 包，可以利用计算集群来提供分布式服务。我们用于自动实现完整 MAGE 对象模型的模型驱动方法提供了高度的灵活性和兼容性。随着微阵列数据的协作分析在国际研究联盟中越来越重要，通过基于 SOAP 的 Web 服务进行数据集成在分布式客户端-服务器环境中具有优势。 EMMA 2 软件设计和实施的充分性已通过其在许多分布式功能基因组学项目中的应用得到证明。其可扩展性使得当前的架构适合于基于高通量测序方法的未来转录组学方法的扩展，这些方法比微阵列具有更高的计算要求。
Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.
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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：
4.1
作者：
Dondrup, M;Goesmann, A;Meyer, F
通讯作者：
Meyer, F
影响因子：
5.8
作者：
Neuweger, Heiko;Albaum, Stefan P.;Goesmann, Alexander
通讯作者：
Goesmann, Alexander
影响因子：
48
作者：
Bammler, T;Beyer, RP;Zarbl, H
通讯作者：
Zarbl, H
影响因子：
14.9
作者：
Barrett T;Troup DB;Wilhite SE;Ledoux P;Rudnev D;Evangelista C;Kim IF;Soboleva A;Tomashevsky M;Marshall KA;Phillippy KH;Sherman PM;Muertter RN;Edgar R
通讯作者：
Edgar R