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Methods to unveil sex-specific genetic architecture in trans-ancestry meta-analysis

Methods to unveil sex-specific genetic architecture in trans-ancestry meta-analysis
在跨祖先荟萃分析中揭示性别特异性遗传结构的方法
批准号:
10681351
负责人:
Bibo Jiang
金额:
$77.98万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-08-10 至 2027-05-31

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中文摘要
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英文摘要
ABSTRACT Large scale genetic datasets have revolutionized human genetic research. In the past decade, genome-wide association studies have identified numerous genetic variants associated with various complex traits. These discoveries have informed new biology and led to novel therapeutics. Yet, most studies focused on European samples and most of the studies were conducted by pooling both sexes together. Sex-specific genetic architecture in diverse populations remains largely elusive. As the next step, consortia efforts have begun to aggregate datasets from diverse non-European populations. Meta-analysis is often employed in large consortium studies There is a compelling need to develop methods that can effectively conduct trans-ancestry meta- analysis. To this end, we will develop a series of innovative methods to improve the power for association mapping, the precision of fine mapping and the accuracy of polygenic predictions in trans -ancestry analysis. Resulting methods will be applied to a series of heart, lung, and blood related traits, in collaboration with a number of consortia studies. This is a continuation of our strong track record of method development in statistical genetics. We will implement the methods into a few widely used tools, including RVTESTS, SEQMINER, and RAREMETAL, which will not only benefit our own study but also other researchers in the field.
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DOI: 10.1093/bioadv/vbad077
发表时间: 2023
期刊: BIOINFORMATICS ADVANCES
影响因子: --
作者: [Palmer, Suzette N., Koh, Andrew Y., Zhan, Xiaowei]
通讯作者: Zhan, Xiaowei
Integrative genomic and geospatial analysis of insurance claim, biobank and GWAS summary statistics for complex traits
Methods to unveil sex-specific genetic architecture in trans-ancestry meta-analysis
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