Mining genome-wide association data to discover and fine-map genomic regions involved in complex traits and disease

挖掘全基因组关联数据以发现和精细绘制涉及复杂性状和疾病的基因组区域

• 批准号: 382604
• 负责人: Bull Shelley B
• 金额: $ 34.44万
• 依托单位: Lunenfeld-Tanenbaum Research Institute (Toronto)
• 依托单位国家: 加拿大
• 项目类别: Operating Grants
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-03-01 至 2022-03-01
• 项目状态: 已结题
• 来源: https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=382604&lang=en
• 关键词: Complex Traits And Disease Phenotypes; Generalized Regression Models; Genome-Wide Studies; Genomic Epidemiology; High-Throughput Genotyping; Human Genomics; Longitudinal Data; Meta-Analysis; Statistical Genomics; Statistical Hypothesis Testing

Investigators of common diseases & traits in human populations can now measure genomic variation at an unprecedented level of detail using advanced technologies, but analytic capacity to integrate & interpret the complex underlying relationships remains l

人类常见疾病和特征的研究人员现在可以使用先进的技术以前所未有的细节水平测量基因组变异，但整合和解释复杂的潜在关系的分析能力仍然不足。