{"title":"Advances and challenges in quantitative delineation of the genetic architecture of complex traits.","authors":"Hua Tang, Zihuai He","doi":"10.15302/j-qb-021-0249","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Genome-wide association studies (GWAS) have been widely adopted in studies of human complex traits and diseases.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":74626,"journal":{"name":"","volume":"9 2 1","pages":"168-184"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9053444/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.15302/j-qb-021-0249","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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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.
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