ashr 2.0.5

Methods for Adaptive Shrinkage, using Empirical Bayes

Released Dec 21, 2016 by Peter Carbonetto

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SQUAREM 2017.10-1 etrunct 0.1 truncnorm 1.0-7 pscl 1.5.2 assertthat 0.2.0 doParallel 1.0.11 Rcpp foreach 1.4.4

The R package 'ashr' implements an Empirical Bayes approach for large-scale hypothesis testing and false discovery rate (FDR) estimation based on the methods proposed in M. Stephens, 2016, "False discovery rates: a new deal", . These methods can be applied whenever two sets of summary statistics---estimated effects and standard errors---are available, just as 'qvalue' can be applied to previously computed p-values. Two main interfaces are provided: ash(), which is more user-friendly; and ash.workhorse(), which has more options and is geared toward advanced users.



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This package was last tested against Renjin 0.8.2543 on Dec 17, 2017.



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