Statistical Genetics of Human Complex Traits
A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Human Genomics and Genetic Diseases".
Deadline for manuscript submissions: closed (20 December 2023) | Viewed by 907
Special Issue Editor
Special Issue Information
Dear Colleagues,
Complex traits, including those of common diseases, are affected by many genetic variants, each explaining a small proportion of phenotypic variance in the population. Over the past decade, genome-wide association studies (GWAS) have successfully identified hundreds of thousands of genetic variants that are associated with a broad range of complex traits and diseases. Although GWAS provide unprecedented opportunities to understand the genetics underpinning complex traits, current challenges lie in how to interpret and apply GWAS discoveries in research and clinical settings. These challenges have motivated the generation of innovative statistical methods and new datasets such as functional genomics and multi-omics data. For example, the “missing heritability” problem in the early stage of GWAS has stimulated the development and application of mixed linear models in large-scale genomic datasets. Moreover, statistical fine-mapping methods incorporating functional genomic information have been developed to identify the causal variants from the non-causals, tagging them by the linkage disequilibrium. More recently, to understand the biological mechanisms through which genetic variants exert their effects on phenotypes, analytical approaches that integrate GWAS data with transcriptomic or epigenomic data have been proposed to detect genes and regulatory elements relevant to these traits. Furthermore, the prediction of individual’s disease risk by polygenic risk score is another exciting application of GWAS data, with great potential in clinical utility. This Special Issue focuses on advances in the development and application of statistical methods for human complex traits.
Dr. Jian Zeng
Guest Editor
Manuscript Submission Information
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Keywords
- statistical genetics
- GWAS
- complex traits
- common diseases
- genetic architecture
- heritability
- polygenic risk prediction
- fine-mapping
- omics
- functional genomics
