Hua Tang1, Zihuai He2,3. 1. Department of Genetics, Stanford University, Stanford, CA 94305, USA. 2. Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA. 3. Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Abstract
Background: Genome-wide association studies (GWAS) have been widely adopted in studies of human complex traits and diseases. Results: This review surveys areas of active research: quantifying and partitioning trait heritability, fine mapping functional variants and integrative analysis, genetic risk prediction of phenotypes, and the analysis of sequencing studies that have identified millions of rare variants. Current challenges and opportunities are highlighted. Conclusion: GWAS have fundamentally transformed the field of human complex trait genetics. Novel statistical and computational methods have expanded the scope of GWAS and have provided valuable insights on the genetic architecture underlying complex phenotypes.
Background: Genome-wide association studies (GWAS) have been widely adopted in studies of human complex traits and diseases. Results: This review surveys areas of active research: quantifying and partitioning trait heritability, fine mapping functional variants and integrative analysis, genetic risk prediction of phenotypes, and the analysis of sequencing studies that have identified millions of rare variants. Current challenges and opportunities are highlighted. Conclusion: GWAS have fundamentally transformed the field of human complex trait genetics. Novel statistical and computational methods have expanded the scope of GWAS and have provided valuable insights on the genetic architecture underlying complex phenotypes.
Entities:
Keywords:
biobank; colocalization; eQTL; genome-wide association study; heritability; polygenic risk scores; rare variants; transcriptome-wide association study
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