GWAS summary statistics for simulated quantitative traits in the UK Biobank (12 configurations)

This dataset contains GWAS summary statistics for quantitative traits simulated based on genotype data for White British samples in the UK Biobank. The dataset is designed to enable systematic PRS analyses across different heritabilities and genetic architectures. For each simulation configuration, we provide GWAS summary statistics for the training, validation, and test sets. The validation summary statistics can be used for model selection/tuning. The test summary statistics can be used to evaluate PRS models via pseudo-validation metrics. Association testing for all simulations and data splits was done with plink2. The simulation configurations included in this dataset span 3 heritability settings and 4 genetic architecture: Heritability settings (proportion of variance explained by typed SNPs): $h_{SNP}^2$ = {0.1, 0.3, 0.5} Polygenicity settings (Proportion of causal variants): $\pi$ = {1%, 0.1%, 0.01%} We also include a simulation of genetic architecture similar to the BayesR model (Sparse GM) where: The variance multipliers: d = [0.0,0.01,0.1,1] The mixing proportions: $\pi$ = [0.995, 0.002, 0.002, 0.001] This means that 99.5% of variants are not causal, etc. For each simulation configuration, we generated 5 independent replicates. Importantly, note that, for each simulation, we also provide the list of causal variants and their simulated effect sizes (these are provided under each replicate, in a file called simulated_effects.txt. The folder structure for each dataset looks as follows: 1 train chr_1.PHENO1.glm.linear ... chr_22.PHENO1.glm.linear test chr_1.PHENO1.glm.linear ... chr_22.PHENO1.glm.linear validation simulated_effects.txt 2 ... 3 4 5 For more details about the GWAS study, Quality Control (QC) criteria, or other information, please consult our publication: Song, J., Zabad, S., Yang, A., Gravel, S., & Li, Y. (2025). Sparse polygenic risk score inference with the spike-and-slab LASSO. Bioinformatics. https://doi.org/10.1093/bioinformatics/btaf578 If you use this data in your work, please cite the publication above.