| Title: | Statistical methods to investigate the regulatory and evolutionary forces shaping the genetics of human traits in diverse UK Biobank populations |
| Lead Institution: | University of Southern California |
| Principal investigator: | Dr Steven Gazal |
Application 68459
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About
While thousands of genetic variants have been associated with human complex traits, the genetic architecture of these traits are poorly understood. Indeed, some fundamental questions, such as linking these associated variants to their target genes, or using these variants to predict disease risk in diverse populations are poorly understood. In this research project, we will develop and/or apply statistical methods that will analyze the impact of genetic variation on human traits and diseases. More precisely, we will (1) analyze genotype-phenotype associations using novel gene-tree-based approaches, (2) link associated variants to their target genes, (3) investigating the impact of natural selection on human traits and diseases, and (4) study the differences in estimated genotype-phenotype associations among distinct populations. We plan to study a wide range of health-related phenotypes, including diseases and quantitative traits, using all the available genetic data, and by stratifying our analyses by UK Biobank populations. Our methods and outcomes will improve our understanding of trait biology, the design of future genetic studies and of downstream analyses to find drug targets for human diseases. All methods and results will be published and made open-source.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 9351 | A scalable approach to characterize pleiotropy across thousands of human diseases and complex traits using GWAS summary statistics | Zixuan Zhang (+5) | 2023 | American Journal of Human Genetics |
Enabling scientific discoveries that improve human health