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Koray Dogan Kaya, Matthew Brooks, Hyun-Jin Yang, Jung-Woong Kim, Gokhan Karakulah, Anand Swaroop; RetSeq: Next Generation Sequencing Database for Exploring Retinal Development, Aging and Disease.. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):1240.
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© ARVO (1962-2015); The Authors (2016-present)
Next generation sequencing technology (NGS) involves massive parallel sequencing that allows global analyses of transcriptomes, regulatory networks and epigenetic modifications. As massive data is being produced in multiple laboratories, we decided to generate a focused database of NGS data from retina (and associated cell types) of humans and model organisms at distinct stages of development, aging and disease conditions. Our goal is to facilitate analyses of biological pathways, disease mechanisms, and targets for drug discovery for retinal and macular diseases.
We collected different types of NGS data from whole retina and distinct retinal cell types. We created a database schema handling those information from different species, mainly from human and mouse. The schema has been constructed via MySQL. We used APACHE web-server for the graphical user interface (GUI). The interface has been written with HTML 5 technology and supported by R statistical environment at the server side. We used Ajax technology with Perl as well to provide as much flexibility as possible for searches. Graphs plotted upon client request can easily be saved as pdf files.
The web interface is shown in Figure 1. As soon as typing user starts typing, the GUI suggests you the genes. If the entered gene symbol is official then the gene counter increases. After the completion of gene selection, the user can chose multiple data to combine. At the end, the user can have figures popped-up instantly. The figures can be converted to pdf via the provided button (Figure 2).
We believe this web-tool will provide a great resource for the vision community. The database is in beta-testing phase, and we hope to make it available to all scientists before ARVO.
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