This application for K01 Mentored Career Development Award in Big Data Science describes a proposal from Dr. J. Eric Schmitt MD, PhD, a neuroradiologist at the University of Pennsylvania. It proposes the development the Integrated Neuroimaging Genomic Ontology Toolbox (INGOT), a free, open source collection of analytic tools for the combined analysis of imaging and genomic data. These tools will include an automated pipeline for combined imaging genomic analysis, the integration of gene and neuroanatomic ontology databases into the analytic framework, and the incorporation of structural equation models to facilitate analysis of genetically- informative longitudinal datasets. These tools will then be tested via simulation and subsequently applied to two large genetically-informative neuroimaging datasets. The proposal also details the continued career development of Dr. Schmitt as he transitions from Neuroradiology Fellow to independent imaging genomics researcher and neuroradiology faculty. A rigorous interdisciplinary curriculum is described, intended to reinforce and update prior training in quantitative neuroimaging and genomics, maintain existing skills in clinical neuroradiology and develop a strong technical skill set in bioinformatics and statistics via a combination of workshops, coursework, and seminars.
Neuroimaging and genomic data are both becoming increasingly complex, hindering the ability of individual researchers to perform statistically rigorous hypothesis-driven analysis. The development of standardized, integrated, intelligent, and open-source analysis tools such as INGOT is critical to the successful fusion of these modalities. INGOT will simplify imaging genomic and longitudinal imaging analysis as well as incorporate information from existing genetic and neuroanatomic databases into the analysis pipeline.
| Jha, Shaili C; Xia, Kai; Schmitt, James Eric et al. (2018) Genetic influences on neonatal cortical thickness and surface area. Hum Brain Mapp 39:4998-5013 |
| Rosen, Adon F G; Roalf, David R; Ruparel, Kosha et al. (2018) Quantitative assessment of structural image quality. Neuroimage 169:407-418 |
| Yushkevich, Paul A; Pashchinskiy, Artem; Oguz, Ipek et al. (2018) User-Guided Segmentation of Multi-modality Medical Imaging Datasets with ITK-SNAP. Neuroinformatics : |
| Roalf, David R; Eric Schmitt, J; Vandekar, Simon N et al. (2017) White matter microstructural deficits in 22q11.2 deletion syndrome. Psychiatry Res Neuroimaging 268:35-44 |
| Schmitt, J Eric; Yi, James; Calkins, Monica E et al. (2016) Disrupted anatomic networks in the 22q11.2 deletion syndrome. Neuroimage Clin 12:420-8 |
