References

Albinana, C., Zhu, Z., Schork, A.J., Ingason, A., Aschard, H., Brikell, I., et al.others. (2022). Multi-PGS enhances polygenic prediction: Weighting 937 polygenic scores. medRxiv. Retrieved from https://doi.org/10.1101/2022.09.14.22279940

Aschard, H., Vilhjálmsson, B.J., Joshi, A.D., Price, A.L., & Kraft, P. (2015). Adjusting for heritable covariates can bias effect estimates in genome-wide association studies. The American Journal of Human Genetics, 96, 329–339.

Bengtsson, H. (2021). A unifying framework for parallel and distributed processing in R using futures. The R Journal, 13, 273–291.

Bybjerg-Grauholm, J., Pedersen, C.B., Bækvad-Hansen, M., Pedersen, M.G., Adamsen, D., Hansen, C.S., et al.others. (2020). The iPSYCH2015 case-cohort sample: Updated directions for unravelling genetic and environmental architectures of severe mental disorders. medRxiv. Retrieved from https://doi.org/10.1101/2020.11.30.20237768

Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L.T., Sharp, K., et al.others. (2018). The UK Biobank resource with deep phenotyping and genomic data. Nature, 562, 203–209.

Chang, C.C., Chow, C.C., Tellier, L.C., Vattikuti, S., Purcell, S.M., & Lee, J.J. (2015). Second-generation PLINK: Rising to the challenge of larger and richer datasets. Gigascience, 4, s13742–015.

Lam, M., Awasthi, S., Watson, H.J., Goldstein, J., Panagiotaropoulou, G., Trubetskoy, V., et al.others. (2020). RICOPILI: rapid imputation for COnsortias PIpeLIne. Bioinformatics, 36, 930–933.

Mak, T.S.H., Porsch, R.M., Choi, S.W., Zhou, X., & Sham, P.C. (2017). Polygenic scores via penalized regression on summary statistics. Genetic Epidemiology, 41, 469–480.

Manichaikul, A., Mychaleckyj, J.C., Rich, S.S., Daly, K., Sale, M., & Chen, W.-M. (2010). Robust relationship inference in genome-wide association studies. Bioinformatics, 26, 2867–2873.

Privé, F. (2021). Optimal linkage disequilibrium splitting. Bioinformatics, 38, 255–256.

Privé, F. (2022). Using the UK Biobank as a global reference of worldwide populations: application to measuring ancestry diversity from GWAS summary statistics. Bioinformatics, 38, 3477–3480.

Privé, F., Albiñana, C., Pasaniuc, B., & Vilhjálmsson, B.J. (2022). Inferring disease architecture and predictive ability with LDpred2-auto. bioRxiv. Retrieved from https://doi.org/10.1101/2022.10.10.511629

Privé, F., Arbel, J., Aschard, H., & Vilhjálmsson, B.J. (2022). Identifying and correcting for misspecifications in GWAS summary statistics and polygenic scores. Human Genetics and Genomics Advances, 3, 100136.

Privé, F., Arbel, J., & Vilhjálmsson, B.J. (2020). LDpred2: better, faster, stronger. Bioinformatics, 36, 5424–5431.

Privé, F., Aschard, H., & Blum, M.G. (2019). Efficient implementation of penalized regression for genetic risk prediction. Genetics, 212, 65–74.

Privé, F., Aschard, H., Carmi, S., Folkersen, L., Hoggart, C., O’Reilly, P.F., & Vilhjálmsson, B.J. (2022). Portability of 245 polygenic scores when derived from the UK Biobank and applied to 9 ancestry groups from the same cohort. The American Journal of Human Genetics, 109, 12–23.

Privé, F., Aschard, H., Ziyatdinov, A., & Blum, M.G.B. (2018). Efficient analysis of large-scale genome-wide data with two R packages: bigstatsr and bigsnpr. Bioinformatics, 34, 2781–2787.

Privé, F., Luu, K., Blum, M.G., McGrath, J.J., & Vilhjálmsson, B.J. (2020). Efficient toolkit implementing best practices for principal component analysis of population genetic data. Bioinformatics, 36, 4449–4457.

Privé, F., Luu, K., Vilhjálmsson, B.J., & Blum, M.G. (2020). Performing highly efficient genome scans for local adaptation with R package pcadapt version 4. Molecular Biology and Evolution, 37, 2153–2154.

Privé, F., Vilhjálmsson, B.J., Aschard, H., & Blum, M.G.B. (2019). Making the most of clumping and thresholding for polygenic scores. The American Journal of Human Genetics, 105, 1213–1221.

Reed, E., Nunez, S., Kulp, D., Qian, J., Reilly, M.P., & Foulkes, A.S. (2015). A guide to genome-wide association analysis and post-analytic interrogation. Statistics in Medicine, 34, 3769–3792.

Visscher, P.M., Wray, N.R., Zhang, Q., Sklar, P., McCarthy, M.I., Brown, M.A., & Yang, J. (2017). 10 years of GWAS discovery: Biology, function, and translation. The American Journal of Human Genetics, 101, 5–22.

Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L.D., François, R., et al.others. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4, 1686.