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Statistical Methods for Next Generation Genome-Wide Association Studies

Statistical Methods for Next Generation Genome-Wide Association Studies
下一代全基因组关联研究的统计方法
批准号:
FT220100069
负责人:
A/Prof Loic Yengo
金额:
$63.05万
依托单位国家:
澳大利亚
项目类别:
ARC Future Fellowships
财政年份:
2023
资助国家:
澳大利亚
项目状态:
未结题
起止时间:
2023-01-01 至 2026-12-31

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中文摘要
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英文摘要
This project aims to develop cutting-edge statistical methods to analyse large genomic datasets and identify genetic variants associated with inter-individual differences in various human traits. Knowledge of trait-associated DNA variants is instrumental in understanding how natural selection has shaped human traits. By integrating genomic data from diverse and underrepresented populations, this project further expects to contribute to the equitable use of genomic technologies in humans, regardless of geographical origins. Expected outcomes of this research include novel analysis methods and software tools, which should broadly and significantly benefit gene discovery in other species, including those of agricultural relevance.
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会议论文
Genetic and Molecular Consequences of Non-Random Mating in Humans
  • 批准号:
    DE200100425
  • 项目类别:
    Discovery Early Career Researcher Award
  • 资助金额:
    $28.12万
  • 财政年份:
    2020
  • 负责人:
    A/Prof Loic Yengo
  • 依托单位:
国内基金
海外基金
Computational Methods for Analyzing Toponome Data