ReviewHeredity2021
Recent innovations and in-depth aspects of post-genome wide association study (Post-GWAS) to understand the genetic basis of complex phenotypes.
Review in Heredity, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 25 citations in OpenAlex.
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- Causal associations between 17 common autoimmune diseases and aortic diseases: a Mendelian randomization study.International journal of cardiology. Cardiovascular risk and prevention · 2025Article
- Linking plant genes to arthropod community dynamics: current progress and future challenges.Plant & cell physiology · 2025Review
- Genome-wide association study of chlamydia reinfection in African American women.Frontiers in immunology · 2025Article
- Genome-wide functional annotation of variants: a systematic review of state-of-the-art tools, techniques and resources.Frontiers in pharmacology · 2025Review
- Cluster effect for SNP-SNP interaction pairs for predicting complex traits.Scientific reports · 2024Article
- Appraisal of Gene-Environment Interactions in GWAS for Evidence-Based Precision Nutrition Implementation.Current nutrition reports · 2022Review
- Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk.American journal of human genetics · 2022Article
- Trade-offs in the genetic control of functional and nutritional quality traits in UK winter wheat.Heredity · 2022Article
- A hidden layer of structural variation in transposable elements reveals potential genetic modifiers in human disease-risk loci.Genome research · 2022Article
- Mutation or not, what directly establishes a neoplastic state, namely cellular immortality and autonomy, still remains unknown and should be prioritized in our research.Journal of Cancer · 2022Review
- Dissecting Meta-Analysis in GWAS Era: Bayesian Framework for Gene/Subnetwork-Specific Meta-Analysis.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the past decade, the high throughput and low cost of sequencing/genotyping approaches have led to the accumulation of a large amount of data from genome-wide association studies (GWASs). The first aim of this review is to highlight how post-GWAS analysis can be used make sense of the obtained associations. Novel directions for integrating GWAS results with other resources, such as somatic mutation, metabolite-transcript, and transcriptomic data, are also discussed; these approaches can help us move beyond each individual data point and provide valuable information about complex trait genetics. In addition, cross-phenotype association tests, when the loci detected by GWASs have significant associations with multiple traits, are reviewed to provide biologically informative results for use in real-time applications. This review also discusses the challenges of identifying interactions between genetic mutations (epistasis) and mutations of loci affecting more than one trait (pleiotropy) as underlying causes of cross-phenotype associations; these challenges can be overcome using post-GWAS analysis. Genetic similarities between phenotypes that can be revealed using post-GWAS analysis are also discussed. In summary, different methodologies of post-GWAS analysis are now available, enhancing the value of information obtained from GWAS results, and facilitating application in both humans and nonhuman species. However, precise methods still need to be developed to overcome challenges in the field and uncover the genetic underpinnings of complex traits.
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