Effectual Database for Gene Expression (EDGE)
To obtain annotations, MAGE-ML exports, and to perform quality control visualizations, and use various normalization methods,
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LIMS for NIDDK Genomics Core Laboratory
The NIDDK microarray LIMS (Laboratory Information Management System) is designed to facilitate the organization, storage, archive, retrieval and analysis of microarray experimental data within a secure environment at NIDDK. It is a scalable, extensible and flexible storage and retrieval system that builds on an Oracle database and an Oracle Application Server using programming languages including Java, XML, HTML, Javascript and PL/SQL. It can interface with statistics software including SAS, S-Plus and common bioinformatics tools such as GeneSpring, Spotfire, and Partek Pro for further analysis of microarray experiment data.
EDGE, or the Effectual Database for Gene Expression, currently resides on a Sun machine (Sun Fire V880 Server, 2 CPU 900 MHz UltraSPARC III Cu, running on Solaris 8). The portal and object components are installed on a separate Linux machine (Dell Optiplex GX240, 1.8 GHz). The LIMS consists of a major database for storage and management of microarray data and associated MIAME and quality control data, as well as other microarray-related databases (such as annotation and sequence databases obtained from various public sources). Currently, data can be retrieved by individual users in a secure manner via a web interface using the Oracle 9iFS internet file system.
Annotation data for the LIMS system is obtained from various sites across the Internet. This is a CRON process that is kicked off at a set frequency. The process is based on a perl program which accesses the known data sources, parses the required information and creates data files locally. The data is then loaded into the Oracle database using either External tables or SQL*Loader.
The ultimate goal for EDGE will be the integration of various high-throughput data types (microarray, real-time pcr, proteomics) and gene annotations from multiple public databases (GenBank, LocusLink, RefSeq, SwissProt, BIND, OMIM, PubMed, dbSNP, etc.) for effective data mining.
Page last updated: January 01, 0001