The wealth, depth and quality of multi-omic data generated through funding from the BRAIN initiative is unprecedented. It ranges from bulk and single cell RNA-seq, to detailed cell type- specific epigenetic analyses throughout development. However, while the technical aspect of obtaining the data is largely resolved, generating biological meaningful information from these multi-faceted datasets remains a great challenge. The long-term goal of our proposal is to allow molecular and cellular neuroscientists to fully benefit from the ever growing wealth of multi-omic data by allowing them to perform basic and complex analyses without having to obtain knowledge in programming. We were recently funded to build a Neuroscience Multi-Omic Data Archive which will host most of the BRAIN initiative multi-omic data (NeMO Archive; R24MH114788). Here we propose to construct the NeMO Analytics ? a work environment that will be fully integrated with the NeMO archives. This will be achieved through a three-tier proposal. First, we will develop the gEAR (gene Expression Analysis Resource - a portal for RNA-seq visualization) to (a) integrate with NeMO archive and other BRAIN initiative data archives; (b) present multi-omic data through integration with Epiviz (an interactive multi-omic genome browser); (c) enable simple and complex cross-dataset analysis; and (d) host the tools developed as part of the proposal. Second, we will generate and apply tools for quantitative reconstruction of gene regulatory networks through integrative analysis and visualization tools and apply them to cortical development. These tools will build on TReNA (a tool for Transcriptional Regulatory Network Analysis) and projectoR. Additional existing tools will be linked to the NeMO Analytics to further enhance the work environment. We will apply these tools to study striatum and inner ear development to serve as real world test cases for using the system. Third we will disseminate the environment to the broader neuroscience community through in person and online hackathons. Successful completion of the project will result in new knowledge, new tools, and most importantly ? long-lasting transformative enhancement of the usability and significance of multi-omic data.
The BRAIN initiative is aimed at revolutionizing the understanding of the human brain. In order to accomplish this goal, a large number of the funded proposals focus on generating multi-omic data. However, many neuroscientists lack the computational training required to achieve systems analysis on these data. To address this concern, we will generate tools that will enable neuroscientists without training in programming to fully explore omic BRAIN Initiative data and resources, and power users, programmatic control through R.
