ArticleNature communications2021
Improved analyses of GWAS summary statistics by reducing data heterogeneity and errors.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 6 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
51 citing papers in PubMed, 6 syntheses or guidelines pooled it, 67 citations in OpenAlex.
- Multi-ancestry genome-wide association analyses of refractive error augment genetic discovery and polygenic prediction.Nature genetics · 2026Pooled it
- A large-scale genome-wide association meta-analysis for nevus count provides direct insights into the genetics of melanoma.Nature communications · 2026Pooled it
- Genome-wide association study of major anxiety disorders in 122,341 European-ancestry cases identifies 58 loci and highlights GABAergic signaling.Nature genetics · 2026Pooled it
- Pooled it
- Pooled it
- CARMA is a new Bayesian model for fine-mapping in genome-wide association meta-analyses.Nature genetics · 2023Pooled it
- Genomic dimensions deconstruct the clinical heterogeneity of bipolar disorder.Research square · 2026Article
- MIXPRS enables multi-population and multi-method polygenic risk scores using summary statistics.Nature genetics · 2026Article
- Hundreds of cardiac MRI traits derived using 3D diffusion autoencoders share a common genetic architecture.Nature communications · 2026Article
- Decoding sequence determinants of gene expression in diverse cellular and disease states.Nature methods · 2026Article
- Establishing standards for genome wide association studies in eusocial insects through a case study in honey bees.Scientific reports · 2026Article
- Simplifying causal gene identification in GWAS loci.PLoS genetics · 2026Article
- Review
- Shared Genetic Susceptibility Between Asthma and Immune-Mediated Inflammatory Diseases.Canadian respiratory journal · 2026Article
- Towards improved fine-mapping of candidate causal variants.Nature reviews. Genetics · 2025Review
- Fast Probabilistic Whitening Transformation for Ultra-High Dimensional Genetic Data.bioRxiv : the preprint server for biology · 2025Article
- Genome-wide association studies identify 77 loci for suicidality and provide novel biological insights.medRxiv : the preprint server for health sciences · 2025Article
- GWAS-informed data integration and non-coding CRISPRi screen illuminate genetic etiology of bone mineral density.Genome biology · 2025Article
- BTS: a scalable Bayesian Tissue Score for prioritizing GWAS variants and their functional contexts across >1000s of omics datasets.Bioinformatics (Oxford, England) · 2025Article
- Combined genome-wide association study of facial traits in Europeans increases explained variance and improves prediction.Nature communications · 2025Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
statistics from genome-wide association studies (GWAS) have facilitated the development of various summary data-based methods, which typically require a reference sample for linkage disequilibrium (LD) estimation. Analyses using these methods may be biased by errors in GWAS summary data or LD reference or heterogeneity between GWAS and LD reference. Here we propose a quality control method, DENTIST, that leverages LD among genetic variants to detect and eliminate errors in GWAS or LD reference and heterogeneity between the two. Through simulations, we demonstrate that DENTIST substantially reduces false-positive rate in detecting secondary signals in the summary-data-based conditional and joint association analysis, especially for imputed rare variants (false-positive rate reduced from >28% to <2% in the presence of heterogeneity between GWAS and LD reference). We further show that DENTIST can improve other summary-data-based analyses such as fine-mapping analysis.
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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.