| Title: | Developing statistical methods for uncovering the genetic basis of complex human diseases |
| Lead Institution: | University of Wisconsin-Madison |
| Principal investigator: | Dr Zhengzheng Tang |
Application 55235
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About
Aim: We will develop novel statistical methods to identify genetic causes of complex human diseases and traits. We propose to develop methods that can integrate large-scale genetics data like UK Biobank datasets with existing multi-omics datasets from consortia such as GTEx and ENCODE. We expect the methods will greatly facilitate prioritizing causal genes and generating targetable mechanistic hypotheses. Scientific rationale: Despite the substantial progress in method development for genetic association analyses, low statistical power and lack of meaningful biological interpretation are still bottlenecks. In order to increase our understanding of the disease mechanisms behind, we will develop methods that are able to leverage the functional information of genetic variants. The application of the novel methods to UK Biobank data will demonstrate the usefulness and generalizability of the methods. Project duration: We expect that we will work on the analyses of data for the next ten years. Public health impact: We expect to be able to provide valuable insight into the understanding of the biology of the wide spectrum of the human complex diseases, and hopefully contribute to new treatment principles, resulting in the development of personalized medicine.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 7907 | Multi-trait analysis of gene-by-environment interactions in large-scale genetic studies. | Lan Luo (+3) | 2023 | Biostatistics |
Enabling scientific discoveries that improve human health