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 accommodate a variety of likelihoods (e.g.,
normal, Poisson) and mixture priors (e.g., uniform, normal).
Matrix, stats, graphics, Rcpp (>= 0.10.5), truncnorm, mixsqp,
SQUAREM, etrunct, invgamma

Matrix, stats, graphics, assertthat, truncnorm, SQUAREM,
doParallel, pscl, Rcpp (>= 0.10.5), foreach, etrunct
testthat, roxygen2, covr, knitr, rmarkdown, ggplot2, REBayes,
Rmosek

Some hypothesis test functions with a focus on non-asymptotic methods that have matching confidence intervals.
stats, exact2x2, exactci, bpcp, ssanv, coin

Some hypothesis test functions (sign test, median and other quantile tests, Wilcoxon signed rank test, coefficient of variation test, test of normal variance, test on weighted sums of Poisson) with a focus on non-asymptotic methods that have matching confidence intervals.

Some hypothesis test functions (sign test, median and other quantile tests, Wilcoxon signed rank test, coefficient of variation test, test of normal variance, test on weighted sums of Poisson, sample size for t-tests with different variances and non-equal n per arm, Behrens-Fisher test) with a focus on non-asymptotic methods that have matching confidence intervals.

Some hypothesis test functions (sign test, median and other quantile tests, Wilcoxon signed rank test, coefficient of variation test, test of normal variance, test on weighted sums of Poisson, sample size for t-tests with different variances and non-equal n per arm, Behrens-Fisher test, nonparametric ABC intervals, Wilcoxon-Mann-Whitney test) with a focus on non-asymptotic methods that have matching confidence intervals.