• EMMA 2--a MAGE-compliant syste...

Treffer: EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data.

Title:
EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data.
Authors:
Dondrup M; Computational Genomics, Center for Biotechnology, Bielefeld University, 33594 Bielefeld, Germany. mdondrup@cebitec.uni-bielefeld.de, Albaum SP, Griebel T, Henckel K, Jünemann S, Kahlke T, Kleindt CK, Küster H, Linke B, Mertens D, Mittard-Runte V, Neuweger H, Runte KJ, Tauch A, Tille F, Pühler A, Goesmann A
Source:
BMC bioinformatics [BMC Bioinformatics] 2009 Feb 06; Vol. 10, pp. 50. Date of Electronic Publication: 2009 Feb 06.
Publication Type:
Journal Article; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105 (Electronic) Linking ISSN: 14712105 NLM ISO Abbreviation: BMC Bioinformatics Subsets: MEDLINE
Imprint Name(s):
Original Publication: [London] : BioMed Central, 2000-
MeSH Terms:
Software*, Gene Expression Profiling/*methods , Oligonucleotide Array Sequence Analysis/*methods, Databases, Genetic ; Genome ; Internet ; User-Computer Interface
References:
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Entry Date(s):
Date Created: 20090210 Date Completed: 20090326 Latest Revision: 20211020
Update Code:
20250114
PubMed Central ID:
PMC2645365
DOI:
10.1186/1471-2105-10-50
PMID:
19200358
Database:
MEDLINE

Weitere Informationen

Background: 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.
Results: 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.
Conclusion: 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.