LFDREmpiricalBayes 1.0

Estimating Local False Discovery Rates Using Empirical Bayes Methods

Released Sep 27, 2017 by Ali Karimnezhad

This package is available for Renjin and there are no known compatibility issues.


R6 2.2.2 matrixStats 0.53.1

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) .



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    <name>bedatadriven public repo</name>

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Test Results

This package was last tested against Renjin 0.9.2644 on Jun 2, 2018.



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