ArticlePLoS genetics2022
Fine-mapping from summary data with the "Sum of Single Effects" model.
Article in PLoS genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 272 papers, 16 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
272 citing papers in PubMed, 16 syntheses or guidelines pooled it.
- Multi-population GWAS meta-analysis identifies bladder cancer susceptibility loci and highlights genetic regulation of smoking-related risk.Nature communications · 2026Pooled it
- Genome-wide analysis implicates inner ear development in Ménière disease.American journal of human genetics · 2026Pooled it
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- Multi-ancestry genome-wide association study of severe pregnancy nausea and vomiting.Nature genetics · 2026Pooled it
- Genome-wide meta-analysis identifies genetic risk loci for mono- and polyneuropathies in 983 477 individuals.Human molecular genetics · 2026Pooled it
- Fine-mapping a genome-wide meta-analysis of 98,374 migraine cases identifies 181 sets of candidate causal variants.Nature communications · 2026Pooled it
- A genome-wide association study of buccal mucosa cancer in India and multi-ancestry meta-analysis discovers risk loci and gene-environment interactions.EBioMedicine · 2025Pooled it
- Computationally efficient meta-analysis of gene-based tests using summary statistics in large-scale genetic studies.Nature genetics · 2025Pooled it
- Genomic loci and molecular genetic mechanisms for hidradenitis suppurativa.The British journal of dermatology · 2025Pooled it
- A contextual genomic perspective on physical activity and its relationship to health, well being and illness.Nature genetics · 2025Pooled it
- Rare genetic variation in PTPRB is associated with central serous chorioretinopathy, varicose veins and glaucoma.Nature communications · 2025Pooled it
- Pooled it
- Trans-ancestry GWAS identifies 59 loci and improves risk prediction and fine-mapping for kidney stone disease.Nature communications · 2025Pooled it
- Integrated genome-wide association studies, meta-analysis, and Bayesian fine mapping reveal novel quantitative trait loci's and functional candidate genes for vulva traits in large white pigs.Journal of animal science · 2025Pooled it
- Multi-ancestry GWAS meta-analyses of lung cancer reveal susceptibility loci and elucidate smoking-independent genetic risk.Nature communications · 2024Pooled it
- Liver eQTL meta-analysis illuminates potential molecular mechanisms of cardiometabolic traits.American journal of human genetics · 2024Pooled it
- Prioritizing context-specific genetic risk mechanisms in 11 solid cancers.Journal of the National Cancer Institute · 2026Article
- Functional characterization of the 9q34.13 locus identifies RAPGEF1 as a candidate gene modulating risk for melanoma and nevi via RAS activation.American journal of human genetics · 2026Article
- Single-cell analysis of chromatin accessibility in the human intestine identifies regulatory programs and clarifies genetic associations in Crohn's disease.Nature genetics · 2026Article
- Article
212 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
In recent work, Wang et al introduced the "Sum of Single Effects" (SuSiE) model, and showed that it provides a simple and efficient approach to fine-mapping genetic variants from individual-level data. Here we present new methods for fitting the SuSiE model to summary data, for example to single-SNP z-scores from an association study and linkage disequilibrium (LD) values estimated from a suitable reference panel. To develop these new methods, we first describe a simple, generic strategy for extending any individual-level data method to deal with summary data. The key idea is to replace the usual regression likelihood with an analogous likelihood based on summary data. We show that existing fine-mapping methods such as FINEMAP and CAVIAR also (implicitly) use this strategy, but in different ways, and so this provides a common framework for understanding different methods for fine-mapping. We investigate other common practical issues in fine-mapping with summary data, including problems caused by inconsistencies between the z-scores and LD estimates, and we develop diagnostics to identify these inconsistencies. We also present a new refinement procedure that improves model fits in some data sets, and hence improves overall reliability of the SuSiE fine-mapping results. Detailed evaluations of fine-mapping methods in a range of simulated data sets show that SuSiE applied to summary data is competitive, in both speed and accuracy, with the best available fine-mapping methods for summary data.
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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.