Administrative supplement for lluminating Neurodevelopment through Integrated Analysis and Visualization of Multi-Omic Data

University Of Maryland Baltimore, Baltimore MD

Investigators

Linked publications & trials

Abstract

PROJECT SUMMARY 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 biologically meaningful information from these multi-faceted datasets remains a great challenge. The parent proposal ?Illuminating Neurodevelopment through Integrated Analysis and Visualization of Multi-Omic Data? is aimed at allowing 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. To achieve this goal, we will utilize NeMO Analytics ? a work environment that will be fully integrated with the NeMO archive (the BRAIN Initiative Neuroscience Multi-Omic Archive) that is currently focused on reference datasets from the developing and adult brain. In this supplement we partner with two expert teams from the Alzheimer?s disease (AD) field ? Dr. Gwenn Garden (University of Washington) and Dr. Ben Logsdon (Sage Bionetworks) to select, import and curate a wealth of high impact multi-omic data from the AD field. In addition to importing the data into the NeMO ecosystem, users will be able to use two analysis and visualization tools built into NeMO Analytics, gEAR and Epiviz. gEAR will allow users to compare gene expression data between multiple datasets, analyze single cell transcriptomic data, and visualize epigenomic data (methylation, chromatin state) in the context of the gene expression data using the integrated Epiviz epigenome browser and analysis tool. NeMO-AD will also allow users to upload their own private data and compare it in the context of the large collection of public data. Finally, we will also work towards broad dissemination of the platform via presentations and workshops in AD scientific meetings. Successful implementation of this supplement will afford meaningful and intuitive access to the wealth of AD-focused data for researchers in the AD domain that are not trained in informatics or programming. This, in turn, will work to further data sharing, hypothesis generation, validation of user- data with existing public data and discovery. It will also broaden the user-base of NeMO Analytics to the AD domain and allow neuroscientists from other fields easy access to AD data for further exploration.