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EBPRS
View on CRAN: Click
here
Download and install EBPRS package within the R console
Install from CRAN:
install.packages("EBPRS")
Install from Github:
library("remotes")
install_github("cran/EBPRS")
Install by package version:
library("remotes")
install_version("EBPRS", "2.1.0")
Attach the package and use:
library("EBPRS")
Maintained by
Shuang Song
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-11-03
Latest Update: 2020-08-26
Description:
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) for a detailed presentation of the method.
How to cite:
Shuang Song (2018). EBPRS: Derive Polygenic Risk Score Based on Emprical Bayes Theory. R package version 2.1.0, https://cran.r-project.org/web/packages/EBPRS. Accessed 06 May. 2025.
Previous versions and publish date:
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Other R packages that EBPRS depends,
imports, suggests or enhances
Complete documentation for EBPRS
Functions, R codes and Examples using
the EBPRS R package
Some associated functions: EBPRS . EBPRSpackage . read_plink . traindat . validate .
Some associated R codes: agtc.R . exdata.R . extractInfo.R . findPara.R . findpara_ltdr.R . generateScore.R . packageEBPRS.R . printAUC.R . read_plink.R . snpEM.R . snpEMrobust.R . validate.R . Full EBPRS package functions and examples
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