R/fdrci-package.R

In fdrci: Permutation-Based FDR Point and Confidence Interval Estimation

#' 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. The package also includes a parametric 
#' analog of the same approach.
#' 
#' \tabular{ll}{ Package: \tab fdrci\cr Type: \tab Package\cr Version: \tab
#' 2.4\cr Date: \tab 2022-10-17\cr License: \tab Artistic-2.0\cr LazyLoad: \tab
#' yes\cr } This method is designed to compute FDR when a permutation-based
#' approach has been utilized. The objective here is to identify a subset of
#' positive tests that have corresponding statistics with a more exteme
#' distribution than the permuted results, which are assumed to represent the
#' null. The significance of the subset is described in terms of the FDR and
#' uncertainty in the FDR estimate by computing a confidence interval. Say a
#' set of p-values(or simply a set of test statistics) were recorded for a set
#' of hypothesis tests, and data were permuted B times with test results
#' generated for each permutation. The function fdr_od() can be used to
#' estimate FDR and and a confidence interval along with pi0, the proportion of
#' true null hypotheses, given a selected significance threshold. The function
#' fdrTbl()uses fdr_od() to create a table of results over a sequence of
#' possible significance thresholds. Finally, the function FDRplot will plot
#' results from fdrTbl(), facilitating the selection of a final significance
#' threshold.
#' 
#' @name fdrci-package
#' @aliases fdrci-package fdrci
#' @docType package
#' @author Joshua Millstein
#' 
#' Maintainer: Joshua Millstein <joshua.millstein@@usc.edu> Joshua Millstein
#' @references Millstein J, Volfson D. 2013. Computationally efficient
#' permutation-based confidence interval estimation for tail-area FDR.
#' Frontiers in Genetics | Statistical Genetics and Methodology 4(179):1-11.
#' 
#' Millstein, J., Battaglin, F., Arai, H., Zhang, W., Jayachandran, P., 
#' Soni, S., Parikh, A.R., Mancao, C. and Lenz, H.J., 2022. fdrci: FDR 
#' confidence interval selection and adjustment for large-scale hypothesis 
#' testing. Bioinformatics advances, 2(1), p.vbac047.
#' @keywords htest nonparametric
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