ArticleF1000Research2021
Performing post-genome-wide association study analysis: overview, challenges and recommendations.
Article in F1000Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
- Multi-ancestry genome-wide association meta-analysis identifies candidate genes for computed tomography-based carcass composition traits in pigs.Genetics, selection, evolution : GSE · 2025Pooled it
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- Age-stratified genomic analyses reveal population-specific genetic determinants of exceptional longevity in Taiwan.GeroScience · 2026Article
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- Genetic Evidence Links Gestational Diabetes Mellitus to Increased ER-Negative Breast Cancer Risk Through a Mendelian Randomization Analysis.International journal of endocrinology · 2026Article
- Meta-sGWAS: Integrating brain spatial interactions to uncover genetic variants in Bipolar Disorder.Research square · 2025Article
- Causal Effect of Blood Cell Perturbation Phenotypes on Multiple Sclerosis via Immune Mediation: A Mendelian Randomization Study.Cellular and molecular neurobiology · 2025Article
- A panoramic view of cotton resistance toiMeta · 2025Article
- Recent advances in omics and the integration of multi-omics in osteoarthritis research.Arthritis research & therapy · 2025Review
- Genome-wide association study of chlamydia reinfection in African American women.Frontiers in immunology · 2025Article
- Second-order group knockoffs with applications to genome-wide association studies.Bioinformatics (Oxford, England) · 2024Article
- Reply to McGowan et al.: An intronic polymorphism associated with 2,3-bisphosphoglycerate levels in human red blood cells is linked to expression of RhCE blood groups.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- EmbedGEM: a framework to evaluate the utility of embeddings for genetic discovery.Bioinformatics advances · 2024Article
- SABER: Statistical Identification of Loci of Interest in GWAS Summary Statistics using a Bayesian Gaussian Mixture Model.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Participation bias in the UK Biobank distorts genetic associations and downstream analyses.Nature human behaviour · 2023Article
- H3AGWAS: a portable workflow for genome wide association studies.BMC bioinformatics · 2022Article
- Benchmarking post-GWAS analysis tools in major depression: Challenges and implications.Frontiers in genetics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 4 countries.
Funding
Abstract
Genome-wide association studies (GWAS) provide huge information on statistically significant single-nucleotide polymorphisms (SNPs) associated with various human complex traits and diseases. By performing GWAS studies, scientists have successfully identified the association of hundreds of thousands to millions of SNPs to a single phenotype. Moreover, the association of some SNPs with rare diseases has been intensively tested. However, classic GWAS studies have not yet provided solid, knowledgeable insight into functional and biological mechanisms underlying phenotypes or mechanisms of diseases. Therefore, several post-GWAS (pGWAS) methods have been recommended. Currently, there is no simple scientific document to provide a quick guide for performing pGWAS analysis. pGWAS is a crucial step for a better understanding of the biological machinery beyond the SNPs. Here, we provide an overview to performing pGWAS analysis and demonstrate the challenges behind each method. Furthermore, we direct readers to key articles for each pGWAS method and present the overall issues in pGWAS analysis. Finally, we include a custom pGWAS pipeline to guide new users when performing their research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.