Semiparametric Methods for Gene-environment Interaction
基因-环境相互作用的半参数方法
基本信息
- 批准号:8663257
- 负责人:
- 金额:$ 33.86万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-07-20 至 2016-04-30
- 项目状态:已结题
- 来源:
- 关键词:AreaCase-Control StudiesCationsCohort StudiesCollectionCommunitiesComputer softwareCoronary heart diseaseCox ModelsCox Proportional Hazards ModelsDataDevelopmentDisease OutcomeEnvironmentEnvironmental ExposureEnvironmental HealthFrequenciesGenesGeneticGenetic screening methodGenomicsGoalsInvestigationJointsKnowledgeLeadLogistic RegressionsMethodologyMethodsModelingNon-Insulin-Dependent Diabetes MellitusOutcomePerformancePopulationPropertyProportional Hazards ModelsPublic HealthRegression AnalysisResearchRoleSamplingScienceStatistical AlgorithmStatistical MethodsTestingWorkabstractingbasecancer typecase controlcohortdensitydisorder riskgene environment interactiongenetic associationgenetic variantgenome wide association studygenome-widehazardhealth science researchhuman diseaseimprovedinterestmalignant breast neoplasmnovelprospectivesimulationuser friendly softwareuser-friendly
项目摘要
DESCRIPTION (provided by applicant): Recent advance of genomic sciences has significantly changed the landscape of environmental health science research. Collection of high throughput genomic data has become increasingly important for investigating the interplay of genes and environment in causing human diseases in environmental case-control and cohort studies. Analysis of such high-dimensional gene-environmental data presents substantial statistical and computational challenges, especially in investigating gene and environment interactions. Limited statistical developments have been made in this area so far. This methodological shortage has become a bottleneck for effectively studying the roles of genes and their interactions with environment in causing human diseases. The purpose of this proposal responds to this need by developing advanced semi-parametric statistical methods to analyze high throughput data from gene and environment studies. We plan (1) to develop semi-parametric locally efficient methods for double-robust estimation in a case-control study, of a model for the joint effect of a genetic factor, an environmental exposure and multiple extraneous confounding factors, (2) to develop semi-parametric methods for multiple robust estimation in cohort and case-control studies, of a model of interaction between a genetic factor and an environmental exposure in the effect that they produce on a binary disease outcome, (3) to develop semi-parametric methods for double robust inferences of genetic effects incorporating gene-environment interaction and confounding adjustment in a Cox proportional hazards model for censored survival data and (4) develop efficient and open access user-friendly algorithms and statistical software that implement these methods with the goal of disseminating them freely to the gene-environment research community. In addition, we will evaluate the performance of our methods in three ongoing GWAS we have been involved with as well as in simulation studies.
描述(申请人提供):基因组科学的最新进展显著改变了环境健康科学研究的格局。在环境病例对照和队列研究中,收集高通量基因组数据对于研究基因和环境在引起人类疾病中的相互作用变得越来越重要。对这种高维基因-环境数据的分析提出了大量的统计和计算挑战,特别是在研究基因和环境的相互作用时。到目前为止,这方面的统计发展有限。这种方法上的不足已经成为有效研究基因及其与环境相互作用在人类疾病中的作用的瓶颈。本提案的目的是通过开发先进的半参数统计方法来分析基因和环境研究的高通量数据来响应这一需求。我们计划(1)在病例对照研究中开发半参数局部有效的双稳健估计方法,用于遗传因素、环境暴露和多种外来混杂因素联合效应的模型;(2)在队列研究和病例对照研究中开发半参数方法用于多重稳健估计,用于遗传因素和环境暴露之间相互作用的模型,它们对二元疾病结果产生影响。(3)开发半参数方法,对基因效应进行双重稳健推断,将基因-环境相互作用和混杂调整纳入审查生存数据的Cox比例风险模型中;(4)开发高效且开放获取的用户友好算法和统计软件,实现这些方法,目标是将它们免费传播给基因-环境研究界。此外,我们将在我们参与的三个正在进行的GWAS以及模拟研究中评估我们的方法的性能。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Eric Joel Tchetgen Tchetgen其他文献
Eric Joel Tchetgen Tchetgen的其他文献
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{{ truncateString('Eric Joel Tchetgen Tchetgen', 18)}}的其他基金
Novel Designs and Methods to Remove Hidden Confounding Bias in Health Sciences
消除健康科学中隐藏的混杂偏差的新颖设计和方法
- 批准号:
10447817 - 财政年份:2020
- 资助金额:
$ 33.86万 - 项目类别:
Novel Designs and Methods to Remove Hidden Confounding Bias in Health Sciences
消除健康科学中隐藏的混杂偏差的新颖设计和方法
- 批准号:
10678962 - 财政年份:2020
- 资助金额:
$ 33.86万 - 项目类别:
Novel Designs and Methods to Remove Hidden Confounding Bias in Health Sciences
消除健康科学中隐藏的混杂偏差的新颖设计和方法
- 批准号:
10159821 - 财政年份:2020
- 资助金额:
$ 33.86万 - 项目类别:
Theory and methods for mediation and interaction
调解和互动的理论和方法
- 批准号:
10092817 - 财政年份:2018
- 资助金额:
$ 33.86万 - 项目类别:
Theory and methods for mediation and interaction
调解和互动的理论和方法
- 批准号:
10328927 - 财政年份:2018
- 资助金额:
$ 33.86万 - 项目类别:
Next Generation Missing Data Methods in HIV Research
HIV 研究中的下一代缺失数据方法
- 批准号:
9636187 - 财政年份:2017
- 资助金额:
$ 33.86万 - 项目类别:
Next Generation Missing Data Methods in HIV Research
HIV 研究中的下一代缺失数据方法
- 批准号:
10092901 - 财政年份:2017
- 资助金额:
$ 33.86万 - 项目类别:
Semiparametric Methods for Gene-environment Interaction
基因-环境相互作用的半参数方法
- 批准号:
8512724 - 财政年份:2012
- 资助金额:
$ 33.86万 - 项目类别:
Semiparametric Methods for Gene-environment Interaction
基因-环境相互作用的半参数方法
- 批准号:
8295644 - 财政年份:2012
- 资助金额:
$ 33.86万 - 项目类别:
Semiparametric Methods for Secondary Outcomes in Case-control Studies
病例对照研究中次要结果的半参数方法
- 批准号:
8214692 - 财政年份:2011
- 资助金额:
$ 33.86万 - 项目类别:
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