Package: LFDREmpiricalBayes 1.0

LFDREmpiricalBayes: Estimating Local False Discovery Rates Using Empirical Bayes Methods

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) <http://hdl.handle.net/10393/34889>.

Authors:Ali Karimnezhad, Johnary Kim, Anna Akpawu, Justin Chitpin and David R Bickel

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NEWS

# Install 'LFDREmpiricalBayes' in R:
install.packages('LFDREmpiricalBayes', repos = c('https://empiricalbayes.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

bayesianmathematicalbiologymultiplecomparison

2.00 score 5 scripts 478 downloads 4 exports 2 dependencies

Last updated 7 years agofrom:e97e0722b0. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-winOKNov 22 2024
R-4.5-linuxOKNov 22 2024
R-4.4-winOKNov 22 2024
R-4.4-macOKNov 22 2024
R-4.3-winOKNov 22 2024
R-4.3-macOKNov 22 2024

Exports:caution.parameter.actionsME.logPRGM.actionSEL.caution.parameter

Dependencies:matrixStatsR6

LFDREmpiricalBayes

Rendered fromLFDREmpiricalBayes.Rnwusingutils::Sweaveon Nov 22 2024.

Last update: 2017-09-27
Started: 2017-09-27