INGOT: a family of statistical computing algorithms for hypothesis-driven imaging genomic and longitudinal neuroimaging analysis

 描述（由申请人提供） 大数据科学K01指导职业发展奖的申请描述了宾夕法尼亚大学神经放射学家J. Eric施密特博士的建议。它建议开发集成神经成像基因组本体论（INGOT），这是一个免费的开源分析工具集合，用于成像和基因组数据的联合分析。这些工具将包括用于组合成像基因组分析的自动化管道，将基因和神经解剖本体数据库整合到分析框架中，以及并入结构方程模型以促进遗传信息纵向数据集的分析。然后，这些工具将通过模拟进行测试，并随后应用于两个大型遗传信息神经成像数据集。该提案还详细说明了施密特博士从神经放射学研究员过渡到独立的成像基因组学研究员和神经放射学教师的持续职业发展。描述了一个严格的跨学科课程，旨在加强和更新定量神经成像和基因组学的先前培训，保持现有的临床神经放射学技能，并通过讲习班，课程和研讨会的组合，在生物信息学和统计学方面发展强大的技术技能。

 DESCRIPTION (provided by applicant) 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.