LFDREmpiricalBayes-package: Estimating Local False Discovery Rates Using Empirical Bayes...

In LFDREmpiricalBayes: Estimating Local False Discovery Rates Using Empirical Bayes Methods

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

Details

Package:	LFDREmpiricalBayes
Type:	Package
Version:	1.0
Date:	2017-09-26
License:	GPL-3
Depends:	R(>= 2.14.2)
Imports:	matrixStats, stats
Suggests:	LFDR.MLE
URL:	https://davidbickel.com

Author(s)

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

Maintainer: Ali Karimnezhad <[e-mail]>

References

Karimnezhad, A. and Bickel, D. R. (2016). Incorporating prior knowledge about genetic variants into the analysis of genetic association data: An empirical Bayes approach. Working paper. Retrieved from http://hdl.handle.net/10393/34889

See Also

For more information on how to interpret the outputs, look at the supplementary file in the vignette directory, "Using the LFDREmpiricalBayes Package."

LFDREmpiricalBayes documentation built on May 2, 2019, 6:38 a.m.