Bumped up version.

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: ashr
 Maintainer: Matthew Stephens <[email protected]>
 Author: Matthew Stephens, Chaoxing Dai, Mengyin Lu, David Gerard, Nan Xiao, Peter Carbonetto
-Version: 2.1-6
+Version: 2.1-7
 Date: 2017-03-15
 Title: Methods for Adaptive Shrinkage, using Empirical Bayes
 Description: 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", <DOI:10.1093/biostatistics/kxw041>. 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. The ash() and ash.workhorse() also provides a flexible modeling interface that can accomodate a variety of likelihoods (e.g., normal, Poisson) and mixture priors (e.g., uniform, normal).