SOLAR-Eclipse Computational Tools for Imaging Genetics

用于遗传学成像的 SOLAR-Eclipse 计算工具

• 批准号: 8698416
• 负责人: PETER V. KOCHUNOV
• 金额: $ 36.31万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2016-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8698416
• 关键词: Accounting; Area; Biological; Brain; Brain imaging; Chromosome Mapping; Complex; Computer software; Data; Data Set; Dependence; Development; Discipline; Disease; Educational workshop; Environment; Epidemiology; Epigenetic Process; Evaluation; Family; Functional Imaging; Funding; Gene Expression; Genes; Genetic; Genetic Markers; Genetic Research; Genotype; Goals; Grant; Heritability; Housing; Human; Image; Image Analysis; Imaging Device; Informatics; Libraries; Linux; Mango - dietary; Manuals; Measurement; Mental disorders; Mentored Research Scientist Development Award; Methods; Methylation; Metric; Modality; Molecular Genetics; National Institute of Biomedical Imaging and Bioengineering; Neurobiology; Neurologic; Neurosciences; Nicotine; Nicotine Dependence; Pathway interactions; Patients; Peer Review; Performance; Phenotype; Procedures; Process; Property; Publications; Publishing; Quantitative Trait Loci; Reproducibility; Research; Resources; Risk; Sampling; Schizophrenia; Science; Science of genetics; Severities; Single Nucleotide Polymorphism; Software Tools; Source Code; Speed; Structure; Testing; United States National Institutes of Health; Work; base; computerized tools; design; disorder risk; e-science; endophenotype; expectation; experience; family structure; flexibility; gene discovery; genetic analysis; genome wide association study; imaging modality; meetings; nervous system disorder; neuroimaging; novel; pleiotropism; simulation; software development; symposium; theories; tool; trait

DESCRIPTION (provided by applicant): This application will provide urgently needed analysis methods to the emerging field of imaging genetics. Our focus is to create SOLAR-Eclipse imaging genetics tools for classical genetic and epigenetic epidemiological analyses such as heritability, pleiotropy, quantitative trait loci (QTL) and genome-wide association (GWAS), gene expression, and methylation analyses using traits derived from structural and functional brain imaging (AIM 1). We will also develop intelligent correction for multiple testing that meets both genetic and imaging requirements (AIM 2). The SOLAR-Eclipse tools will be optimized to use voxel-wise brain functional and structural imaging traits and high throughput modern molecular genetic data. The proposed tools will be flexible to accommodate both structured family-based and unstructured epidemiological samples. These tools will be released as a standalone application and integrated into the existing neuroscience eScience networks. Achieving this goal in a single analysis package will greatly enhance and speed up the search for genes that influence brain's neuroanatomic and functional traits and provide comprehensive tools to illustrate pathways from genes to brain structure/function. During the development process we will test and optimize these tools (AIM 3) using the data generated by three NIH-funded imaging genetics projects, the Genetic of Brain Structure, the Human Connectom project, and the NicotineBrain. The tools, source codes and documented analyses strategies will be distributed via the Neuroimaging Informatics Tool and Resources Clearing house (NITRC.org). The PI for this application is a NIBIB-funded K-awardee who has worked on optimizing the standard genetic analysis methods for imaging genetics research. This work generated twenty-five peer- reviewed publications in the last four years. These experiences will be used to create a new library of tools termed, SOLAR-Eclipse, which will be based on the NIH-funded SOLAR library of statistical genetic methods. Our preliminary data shows that when optimized for imaging traits these tools can achieve 100-200 fold performance improvement (over standard methods) enabling full scale (~105 traits in 103 subjects) voxel-wise univariate and bivariate genetic analyses on a multi-node Linux cluster. The collaborators on this grant combine experts in imaging and genetics who have demonstrated their experience in developing tools in both domains and developed popular analyses tools such as SOLAR, FSL, SPM, BrainMap, Talairach Daemon, JIST, Mango and others.

描述（由申请人提供）：本申请将为新兴的成像遗传学领域提供急需的分析方法。我们的重点是创建SOLAR-Eclipse成像遗传学工具，用于经典的遗传和表观遗传流行病学分析，如遗传力，多效性，数量性状位点（QTL）和全基因组关联（GWAS），基因表达和甲基化分析，使用来自结构和功能脑成像（AIM 1）的性状。我们还将为满足遗传和成像要求的多项测试开发智能校正（AIM 2）。SOLAR-Eclipse工具将进行优化，以使用体素脑功能和结构成像特征以及高通量现代分子遗传数据。拟议的工具将是灵活的，以适应结构化的家庭为基础的和非结构化的流行病学样本。这些工具将作为独立的应用程序发布，并集成到现有的神经科学eScience网络中。在一个单一的分析包中实现这一目标将大大增强和加快对影响大脑神经解剖和功能特征的基因的搜索，并提供全面的工具来说明从基因到大脑结构/功能的途径。在开发过程中，我们将使用NIH资助的三个成像遗传学项目（脑结构遗传学项目、人类连接组织项目和尼古丁脑项目）生成的数据测试和优化这些工具（AIM 3）。工具、源代码和记录的分析策略将通过神经影像学信息工具和资源交换所（NITRC. org）分发。本申请的PI是NIBIB资助的K获奖者，他致力于优化成像遗传学研究的标准遗传分析方法。这项工作在过去四年中产生了二十五篇同行评审的出版物。这些经验将用于创建一个新的工具库，称为SOLAR-Eclipse，它将基于NIH资助的统计遗传方法的SOLAR库。我们的初步数据表明，当针对成像性状进行优化时，这些工具可以实现100-200倍的性能改进（超过标准方法），从而能够在多节点Linux集群上进行全尺度（103个受试者中的~105个性状）体素单变量和双变量遗传分析。这项资助的合作者联合收割机结合了成像和遗传学方面的专家，他们在这两个领域开发工具方面都有丰富的经验，并开发了流行的分析工具，如SOLAR，FSL，SPM，BrainMap，Talairach Daemon，JIST，Mango等。