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DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Datgan, a reusable software system for facile interrogation and visualization of complex transcription profiling

Gareth R Howell¹, David O Walton, Benjamin L King

¹The Howard Hughes Medical Institute, Bar Harbor, Maine, USA.

|August 26, 2011

Summary

Glaucoma Discovery Platform (GDP) and Datgan scripts offer easy access to glaucoma transcription data. This tool aids in understanding disease progression through interactive data exploration and analysis.

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Area of Science:

Genomics
Bioinformatics
Ophthalmology

Background:

Introduces the Glaucoma Discovery Platform (GDP), an online environment for visualizing and analyzing complex glaucoma transcription profiling datasets.
Reports the availability of Datgan, a suite of scripts used to build the GDP.
Positions GDP as a complementary tool to existing repositories like NCBI GEO and EBI ArrayExpress, enabling searchable databases for enhanced dataset understanding.

Purpose of the Study:

To develop an accessible online platform for detailed analysis of glaucoma-related gene expression data.
To provide a user-friendly interface for interrogating transcription profiling datasets in glaucoma research.
To enable the identification of early molecular changes in glaucoma through advanced data analysis.

Main Methods:

Utilized Datgan scripts to construct the data tables and web interface for GDP.
Employed a mouse model of glaucoma (DBA/2J strain) and a genetically matched control (DBA/2J-Gpnmb+ strain).
Assessed both retinal and optic nerve head tissues, applying hierarchical clustering to identify molecular stages of glaucoma.

Main Results:

GDP features an interactive component for assessing genes of interest across disease stages in retina and optic nerve head.
Outputs are provided in graphical and tabular formats, highlighting statistically significant differences.
A bulk download component allows retrieval of differentially expressed gene lists compatible with Excel.
GDP links to external resources like Mouse Genome Informatics and OMIM for comprehensive gene information.

Conclusions:

Datgan-constructed databases facilitate user-friendly access to temporally ordered disease or developmental stage datasets.
Datgan and GDP are publicly available for use in glaucoma research.
The platform enhances the understanding of glaucoma pathogenesis through accessible data analysis.