Permutation-based FDR Point and Confidence Interval Estimation
FDR functions for permutation-based estimators, including
pi0 as well as FDR confidence intervals. The confidence
intervals account for dependencies between tests by the
incorporation of an overdispersion parameter, which is
estimated from the permuted data.

FDR functions for permutation-based estimators, including pi0 as well as FDR
confidence intervals. The confidence intervals account for dependencies between
tests by the incorporation of an overdispersion parameter, which is estimated
from the permuted data.

Permutation-Based FDR Point and Confidence Interval Estimation

person(
"Joshua", "Millstein", email = "joshua.millstein@usc.edu",
role = c("aut", "cre"))

FDR functions for permutation-based estimators, including pi0 as well as FDR
confidence intervals. The confidence intervals account for dependencies between
tests by the incorporation of an overdispersion parameter, which is estimated
from the permuted data. Also included are options for an analog parametric approach.
rmarkdown, knitr, GEOquery, dplyr, foreach

Estimation and Control of (Local) False Discovery Rates
This packages contains utility functions for
controlling and estimating (local) false discovery rates,
including some diagnostic plots to support the choice of
the most suitable fdr method.

This package allows to estimate both tail area-based
false discovery rates (Fdr) as well as local false discovery rates (fdr)
for a variety of null models (p-values, z-scores, correlation coeficients,
t-statistics).  The proportion of null values and the parameters
of the null distribution are adaptively estimated from the data.
In addition, the package contains unctions for non-parametric density
estimation (Grenander estimator), for monotonic regression, for
computing the greatest convex minorant (GCM) and the least concave
majorant (LCM), and for the half-normal and correlation distribution.

This package allows to estimate both tail area-based
false discovery rates (Fdr) as well as local false discovery rates (fdr)
for a variety of null models (p-values, z-scores, correlation coeficients,
t-statistics).  The proportion of null values and the parameters
of the null distribution are adaptively estimated from the data.
In addition, the package contains functions for non-parametric density
estimation (Grenander estimator), for monotonic regression, for
computing the greatest convex minorant (GCM) and the least concave
majorant (LCM), and for the half-normal and correlation distribution.