A Novel Bayesian Model Averaging Approach for Genome Wide Association Studies

用于全基因组关联研究的新型贝叶斯模型平均方法

• 批准号: 8182516
• 负责人: MICHAEL D SWARTZ
• 金额: $ 3.08万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2012-07-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8182516
• 关键词: Address; Age; Algorithms; Bayesian Method; Bioinformatics; Biological; Biological Models; Cancer Center; Candidate Disease Gene; Cell physiology; Clinical; Code; Communities; Complex; Data; Data Set; Disease; Epidemiology; Ethnic Origin; Family Cancer History; First Degree Relative; Gender; Genes; Genetic; Genetic Counseling; Genetic Markers; Genetic Predisposition to Disease; Genetic Structures; Genome; Genome Scan; Grant; Individual; Knowledge; Lead; Left; Linkage Disequilibrium; Logistic Regressions; Malignant Neoplasms; Malignant neoplasm of lung; Markov Chains; Methodological Studies; Methods; Modeling; Pathway interactions; Pattern; Prevention Research; Prevention strategy; Process; Proteins; Recording of previous events; Relative (related person); Reporting; Research; Research Personnel; Risk; Sample Size; Sampling; Simulate; Single Nucleotide Polymorphism; Smoker; Smoking; Staging; Structure; Techniques; Testing; Texas; Tobacco; Trust; Uncertainty; Universities; alcohol exposure; cancer prevention; case control; design; disorder risk; drinking; falls; gene discovery; genetic analysis; genetic association; genetic risk factor; genome wide association study; genome-wide; indexing; insight; lung cancer prevention; mathematical model; novel; prevent; response; simulation; success; tool; trait