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__NOTOC__
Michael Dondrup, Alexander Goesmann

'''''EMMA 2 - A MAGE-compliant system for storage and analysis of
microarray data'''''

===== Short abstract =====
EMMA is a web-based software system for
management and analysis of transcriptomic data. EMMA 2 now supports the
complete MAGE-ML format for data import and export. EMMA allows
mapping of gene expression data onto proteome data or pathways and
vice versa and provides extensible analysis and visualization Plug-Ins via the
R-language.

===== Long abstract =====

Apart from efficient storage, state-of-the-art algorithms and visualizations
interpretation of data from microarrays often requires mapping
large datasets onto a variety of genomic data sources. Here we describe
the EMMA 2 software which is a repository for array-related data as
well as a tool for automated analysis using routine pipelines.

EMMA is capable of importing and exporting the contents of its
repository via MAGE-ML.
Interchanging data either with other
software or between institutions is a crucial step during analysis or
publication of results. Thus EMMA 2 supports the complete MAGE-ML
standard and can be used to gather microarray data from a variety of
sources. Since the complete MAGE object model is fairly complex,
the standard user-interface simplifies access
by hiding the details of the model, while a MAGE-editor provides
access to every detail when needed.
Measured data can be exported in a variety of formats
including binary data files like NetCDF and HDF5.
EMMA is written mainly in Perl while portions are in R and
Java.

The repository is implemented using O2DBI, which is a object-oriented code
generator. O2DBI significantly simplifies the creation of complex
database applications. Additionally the repository provides role-based access control for
each data-object.

EMMA 2 offers the ability to describe experiments in a MIAME compliant
way. Instead of relying simply on free-text descriptions,
workflows can be described using a graphical workflow
editor which allows to create customized protocols and to translate
them into MAGE.

EMMA provides an interface to the statistical package R for data
analysis. All methods available through the R-language can be made
available to EMMA. Predefined methods for normalization, testing for
differentially expressed genes and clustering exist. These methods can
be arranged in pipelines and are sent to a batch-queuing system to
utilize CPU-clusters parallel computation.

EMMA can visualize measured data for both quality control and
analysis. If provided with the scanned images several types of
quality control images can be computed.
2D-scatter plots of normalized and non-normalized data can be created.
Additionally 3D-scatter plots and 3D-visualizations of self-organizing maps are
available via a Java-application or VRML-Plug-In.

EMMA 2 can communicate with other software like the genome annotation
system GenDB, the proteomics software ProDB or the pathway viewer
GoPARC via the BRIDGE system. This allows EMMA to map eg. genetic
location or pathway information into several visualizations. On the other hand
it provides other applications with expression data. Expression
profiles can for instance be mapped onto genetic loci by GenDB.

AbstractISMB2004 - Revision history

Admin: 2 revisions

imported>MichaelDondrup at 14:27, 28 April 2004

Unknown user at 00:00, 1 January 1970