We characterized the genetics of 35 biomarkers in UK Biobank. We performed the association and fine-mapping analysis to prioritize the causal variants, constructed the polygenic risk score (PRS) models, and evaluated their medical relevance with causal inference and PRS-PheWAS. We demonstrate a new approach, called multi-PRS, to improve PRS by combining PRSs across traits.
- GWAS summary statistics is available on GWAS catalog
We uploaded the supplementary data on figshare.
- GWAS summary statistics
- Title: The meta-analyzed GWAS summary statistics for 35 lab biomarkers described in 'Genetics of 35 blood and urine biomarkers in the UK Biobank'
- DOI: https://doi.org/10.35092/yhjc.12355382
- snpnet
- Title: The snpnet polygenic risk score coefficients for 35 lab biomarkers described in 'Genetics of 35 blood and urine biomarkers in the UK Biobank'
- DOI: https://doi.org/10.35092/yhjc.12298838
- multi-PRS
- Title: The multi-PRS weights computed with the 35 lab biomarkers described in 'Genetics of 35 blood and urine biomarkers in the UK Biobank'
- DOI: https://doi.org/10.35092/yhjc.12355424
covariate_correction: (for adjusting for statins and covariates)snakemake: (for running the GWAS)filtration: (for filtering GWAS results)meta: (meta-analysis of the GWAS from multiple populations)meta_flipfix: (flipping alleles on the meta-analysis)cascade: (plotting of the variant effects)phewas: (testing against other traits)
snpnet: (generation of polygenic risk scores)
- Phenotype file location
- Residual:
@@@@@@/projects/biomarkers/covariate_corrected/outputExtendedNoTDIreduced/phenotypes/combined.20190810.phe
- Residual:
- GWAS summary statistics
@@@@@@/projects/biomarkers_rivas/main/<population>/ukb24983_v2_hg19.<trait>.genotyped.glm.linear.gz
- M-A
@@@@@@/projects/biomarkers_rivas/meta_flipfixed/METAANALYSIS_<trait>_1.tbl.gz