Illuminating Neurodevelopment Through Integrated Analysis and Visualization of Multi-Omic Data
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. Most of these data are now stored in the Neuroscience Multi-Omic (NeMO) Archive.
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.
NeMO Analytics is a work environment that will be fully integrated with the NeMO archives to allow meaningful access to multi-omic data. 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; umgear.org) 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.
Project Leadership
Ronna Hertzano, M.D., Ph.D. (Principal Investigator)
Associate Professor, Department of Otorhinolaryngology, Head and Neck Surgery
Associate Professor, Department of Anatomy and Neurobiology
Affiliate Member, Institute for Genome Sciences
University of Maryland School of Medicine
https://www.medschool.umaryland.edu/profiles/Hertzano-Ronna/
https://hertzanolab.org
Owen White, M.D., Ph.D. (MPI)
Professor, Epidemiology & Public Health
Associate Director, Institute for Genome Sciences; Director of the UM Center for Health-Related Informatics and Bioimaging (CHIB)
University of Maryland School of Medicine
https://www.medschool.umaryland.edu/profiles/White-Owen/
Seth Ament, Ph.D. (Co-investigator)
Assistant Professor, Psychiatry
University of Maryland School of Medicine
https://www.medschool.umaryland.edu/profiles/Seth-Ament/
Project Data Types
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NeMO Analytics (nemoanalytics.org) is a web-based suite of data visualization and analysis tools, focused on single-cell data analysis. The portal allows users to visualize published or user-supplied multi-omic data across experiments and species side-by-side. Tools include cluster visualization based on expression/cell type, cluster comparison, projection of one dataset into another, identification of marker genes, comparison of marker genes across datasets and note taking.
Related Resources
- NeMO Analytics: https://nemoanalytics.org/