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LFDREmpiricalBayes  

Estimating Local False Discovery Rates Using Empirical Bayes Methods
View on CRAN: Click here


Download and install LFDREmpiricalBayes package within the R console
Install from CRAN:
install.packages("LFDREmpiricalBayes")

Install from Github:
library("remotes")
install_github("cran/LFDREmpiricalBayes")

Install by package version:
library("remotes")
install_version("LFDREmpiricalBayes", "1.0")



Attach the package and use:
library("LFDREmpiricalBayes")
Maintained by
Ali Karimnezhad
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-09-27
Latest Update: 2017-09-27
Description:
New empirical Bayes methods aiming at analyzing the association of single nucleotide polymorphisms (SNPs) to some particular disease are implemented in this package. The package uses local false discovery rate (LFDR) estimates of SNPs within a sample population defined as a "reference class" and discovers if SNPs are associated with the corresponding disease. Although SNPs are used throughout this document, other biological data such as protein data and other gene data can be used. Karimnezhad, Ali and Bickel, D. R. (2016) .
How to cite:
Ali Karimnezhad (2017). LFDREmpiricalBayes: Estimating Local False Discovery Rates Using Empirical Bayes Methods. R package version 1.0, https://cran.r-project.org/web/packages/LFDREmpiricalBayes. Accessed 24 Oct. 2026.
Previous versions and publish date:
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Complete documentation for LFDREmpiricalBayes
Functions, R codes and Examples using the LFDREmpiricalBayes R package
Some associated functions: LFDREmpiricalBayes-package . ME.log . PRGM.action . SEL.caution.parameter . caution.parameter.actions . 
Some associated R codes: ME.Method.R . PRGM.action.R . SEL.caution.parameter.R . caution.parameter.actions.R .  Full LFDREmpiricalBayes package functions and examples
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