EBPRS
Derive Polygenic Risk Score Based on Emprical Bayes Theory
EB-PRS is a novel method that leverages information for effect sizes across all the markers to improve the prediction accuracy. No parameter tuning is needed in the method, and no external information is needed. This R-package provides the calculation of polygenic risk scores from the given training summary statistics and testing data. We can use EB-PRS to extract main information, estimate Empirical Bayes parameters, derive polygenic risk scores for each individual in testing data, and evaluate the PRS according to AUC and predictive r2. See Song et al. (2020) doi:10.1371/journal.pcbi.1007565 for a detailed presentation of the method.
- Version2.1.0
- R version≥ 3.5.0
- LicenseGPL-3
- Needs compilation?No
- Last release08/26/2020
Team
Shuang Song
Wei Jiang
Show author detailsRolesAuthorHongyu Zhao
Show author detailsRolesAuthorLin Hou
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 323 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
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Last 365 days
This package has been downloaded 3,973 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 47 downloads.
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Dependencies
- Depends3 packages