p.fdr: FDR Computation
In FDRestimation: Estimate, Plot, and Summarize False Discovery Rates

View source: R/p.fdr.R

p.fdr

R Documentation

FDR Computation

Description

This function computes FDRs and Method Adjusted p-values.

Usage

p.fdr(
  pvalues = NA,
  zvalues = "two.sided",
  threshold = 0.05,
  adjust.method = "BH",
  BY.corr = "positive",
  just.fdr = FALSE,
  default.odds = 1,
  estim.method = "set.pi0",
  set.pi0 = 1,
  hist.breaks = "scott",
  ties.method = "random",
  sort.results = FALSE,
  na.rm = TRUE
)

Arguments

`pvalues`	A numeric vector of raw p-values.
`zvalues`	A numeric vector of z-values to be used in pi0 estimation or a string with options "two.sided", "greater" or "less". Defaults to "two.sided".
`threshold`	A numeric value in the interval `[0,1]` used in a multiple comparison hypothesis tests to determine significance from the null. Defaults to 0.05.
`adjust.method`	A string used to identify the p-value and false discovery rate adjustment method. Defaults to `BH`. Options are `BH`, `BY`, codeBon,`Holm`, `Hoch`, and `Sidak`.
`BY.corr`	A string of either "positive" or "negative" to determine which correlation is used in the BY method. Defaults to `positive`.
`just.fdr`	A Boolean TRUE or FALSE value which output only the FDR vector instead of the list output. Defaults to FALSE.
`default.odds`	A numeric value determining the ratio of pi1/pi0 used in the computation of one FDR. Defaults to 1.
`estim.method`	A string used to determine which method is used to estimate the null proportion or pi0 value. Defaults to `set.pi0`.
`set.pi0`	A numeric value to specify a known or assumed pi0 value in the interval `[0,1]`. Defaults to 1. Which means the assumption is that all inputted raw p-values come from the null distribution.
`hist.breaks`	A numeric or string variable representing how many breaks are used in the pi0 estimation histogram methods. Defaults to "scott".
`ties.method`	A string a character string specifying how ties are treated. Options are "first", "last", "average", "min", "max", or "random". Defaults to "random".
`sort.results`	A Boolean TRUE or FALSE value which sorts the output in either increasing or non-increasing order dependent on the FDR vector. Defaults to FALSE.
`na.rm`	A Boolean TRUE or FALSE value indicating whether NA's should be removed from the inputted raw p-value vector before further computation. Defaults to TRUE.

Details

We run into errors or warnings when pvalues, zvalues, threshold, set.pi0, BY.corr, or default.odds are not inputted correctly.

Value

A list containing the following components:

`fdrs`	A numeric vector of method adjusted FDRs.
`Results Matrix`	A numeric matrix of method adjusted FDRs, method adjusted p-values, and raw p-values.
`Reject Vector`	A vector containing Reject.H0 and/or FTR.H0 based off of the threshold value and hypothesis test on the adjusted p-values.
`pi0`	A numeric value for the pi0 value used in the computations.
`threshold`	A numeric value for the threshold value used in the hypothesis tests.
`Adjustment Method`	The string with the method name used in computation(needed for the plot.fdr function).

References

\insertRef

Rpack:bibtexRdpack

\insertRef

RFDRestimation

\insertRef

efron:2013FDRestimation

\insertRef

bh:1995FDRestimation

\insertRef

shaffer:1995FDRestimation

\insertRef

storey:2003FDRestimation

\insertRef

by:2001FDRestimation

\insertRef

mein:2006FDRestimation

\insertRef

jiang:2008FDRestimation

\insertRef

nett:2006FDRestimation

\insertRef

pounds:2003FDRestimation

\insertRef

holm:1979FDRestimation

\insertRef

bon:1936FDRestimation

\insertRef

hoch:1988FDRestimation

\insertRef

sidak:1967FDRestimation

\insertRef

murray2020falseFDRestimation

Examples


# Example 1
pi0 = 0.8
pi1 = 1-pi0
n = 10000
n.0 = ceiling(n*pi0)
n.1 = n-n.0

sim.data = c(rnorm(n.1,3,1),rnorm(n.0,0,1))
sim.data.p = 2*pnorm(-abs(sim.data))

fdr.output = p.fdr(pvalues=sim.data.p, adjust.method="BH")

fdr.output$fdrs
fdr.output$pi0

# Example 2

sim.data.p = output = c(runif(800),runif(200, min=0, max=0.01))
fdr.output = p.fdr(pvalues=sim.data.p, adjust.method="Holm", sort.results = TRUE)

fdr.output$`Results Matrix`

FDRestimation documentation built on April 1, 2022, 5:07 p.m.