Email updates

Keep up to date with the latest news and content from BMC Genomics and BioMed Central.

Open Access Database

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

Gareth R Howell12, David O Walton2, Benjamin L King3, Richard T Libby4 and Simon WM John125*

Author Affiliations

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

2 The Jackson Laboratory, 600 Main Street, Bar Harbor, Maine, USA

3 Mount Desert Island Biological Laboratory, Salisbury Cove, ME, USA

4 University of Rochester Eye Institute, University of Rochester Medical Center, Rochester, NY, USA

5 Department of Ophthalmology, Tufts University of Medicine, Boston, MA, USA

For all author emails, please log on.

BMC Genomics 2011, 12:429  doi:10.1186/1471-2164-12-429

Published: 24 August 2011

Abstract

Background

We introduce Glaucoma Discovery Platform (GDP), an online environment for facile visualization and interrogation of complex transcription profiling datasets for glaucoma. We also report the availability of Datgan, the suite of scripts that was developed to construct GDP. This reusable software system complements existing repositories such as NCBI GEO or EBI ArrayExpress as it allows the construction of searchable databases to maximize understanding of user-selected transcription profiling datasets.

Description

Datgan scripts were used to construct both the underlying data tables and the web interface that form GDP. GDP is populated using data from a mouse model of glaucoma. The data was generated using the DBA/2J strain, a widely used mouse model of glaucoma. The DBA/2J-Gpnmb+ strain provided a genetically matched control strain that does not develop glaucoma. We separately assessed both the retina and the optic nerve head, important tissues in glaucoma. We used hierarchical clustering to identify early molecular stages of glaucoma that could not be identified using morphological assessment of disease. GDP has two components. First, an interactive search and retrieve component provides the ability to assess gene(s) of interest in all identified stages of disease in both the retina and optic nerve head. The output is returned in graphical and tabular format with statistically significant differences highlighted for easy visual analysis. Second, a bulk download component allows lists of differentially expressed genes to be retrieved as a series of files compatible with Excel. To facilitate access to additional information available for genes of interest, GDP is linked to selected external resources including Mouse Genome Informatics and Online Medelian Inheritance in Man (OMIM).

Conclusion

Datgan-constructed databases allow user-friendly access to datasets that involve temporally ordered stages of disease or developmental stages. Datgan and GDP are available from http://glaucomadb.jax.org/glaucoma webcite.