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Bayesian Multi-SNP Genetic Association Analysis: Control of FDR and Use of Summary Statistics
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Efficient Integrative Multi-SNP Association Analysis via Deterministic Approximation of Posteriors
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Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits
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Bayesian refinement of association signals for 14 loci in 3 common diseases
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Approximately independent linkage disequilibrium blocks in human populations
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Bayesian model selection in complex linear systems, as illustrated in genetic association studies
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Controlling the false discovery rate via knockoffs
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Molecular QTL discovery incorporating genomic annotations using Bayesian false discovery rate control
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Bayesian large-scale multiple regression with summary statistics from genome-wide association studies
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GUESS-ing Polygenic Associations with Multiple Phenotypes Using a GPU-Based Evolutionary Stochastic Search Algorithm
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Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics
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Integrating Functional Data to Prioritize Causal Variants in Statistical Fine-Mapping Studies
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Cross-Population Joint Analysis of eQTLs: Fine Mapping and Functional Annotation
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Integrating molecular QTL data into genome-wide genetic association analysis: Probabilistic assessment of enrichment and colocalization
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Identifying Causal Variants at Loci with Multiple Signals of Association
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Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics
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Controlling the Rate of GWAS False Discoveries
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A Unified View of False Discovery Rate Control: Reconciliation of Bayesian and Frequentist Approaches
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