The Howard Hughes Medical Institute, Bar Harbor, Maine, USA.
BMC Genomics. 2011 Aug 24;12:429. doi: 10.1186/1471-2164-12-429.
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.
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).
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.
我们介绍了青光眼发现平台（GDP），这是一个用于方便地可视化和查询复杂转录谱数据集的在线环境，用于青光眼研究。我们还报告了 Datgan 的可用性，这是一组用于构建 GDP 的脚本。这个可重复使用的软件系统补充了现有的存储库，如 NCBI GEO 或 EBI ArrayExpress，因为它允许构建可搜索的数据库，以最大限度地理解用户选择的转录谱数据集。
Datgan 脚本用于构建 GDP 的基础数据表和网页界面。GDP 使用来自青光眼小鼠模型的数据填充。这些数据是使用 DBA/2J 品系生成的，DBA/2J 是一种广泛用于青光眼的小鼠模型。DBA/2J-Gpnmb+ 品系提供了一个遗传匹配的对照品系，不会发展为青光眼。我们分别评估了视网膜和视神经头部这两个在青光眼研究中非常重要的组织。我们使用层次聚类来识别早期的分子阶段，这些阶段无法通过疾病的形态学评估来识别。GDP 有两个组成部分。首先，一个交互式搜索和检索组件提供了在视网膜和视神经头部的所有疾病识别阶段评估感兴趣基因的能力。输出以图形和表格格式返回，具有统计学意义的差异突出显示，便于直观分析。其次，批量下载组件允许将差异表达基因的列表作为一系列与 Excel 兼容的文件检索。为了方便访问感兴趣基因的其他可用信息，GDP 链接到选定的外部资源，包括 Mouse Genome Informatics 和 Online Medelian Inheritance in Man (OMIM)。
Datgan 构建的数据库允许用户友好地访问涉及疾病或发育阶段的时间顺序阶段的数据集。Datgan 和 GDP 可从 http://glaucomadb.jax.org/glaucoma 获得。
