snpboost - Boosting Polygenic Risk Scores

To fit polygenic risk scores (PRS) directly on individual-level genotype data, we developed the adapted statistical boosting framework snpboost which is implemented in R and available open source ( The algorithm is batch-based, i.e. we iteratively work on batches of variants to reduce computational complexity. Statistical boosting fits a multivariable regression, i.e. all genetic information is taken into account simultaneously instead of looking at each SNP separately. While the snpboost framework has been introduced (, we are currently working on extending the framework to fit different outcomes or phenotypes (including time-to-event outcomes and quantile regression) and to include further effects (e.g. non-linear effects and SNP-SNP interactions). This is joint work with the Institute of Medical Biometry, Informatics and Epidemiology, Bonn University, and the Center for Human Genetics, Philipps-University Marburg.

© Hannah Klinkhammer
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