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Last data update: 2014.03.03

R: Estimation of the false discovery rate.

LBE	R Documentation

Estimation of the false discovery rate.

Description

LBE is an efficient procedure for estimating the proportion of true null hypotheses, the false discovery rate and the q-values.

Usage

LBE(pval, a = NA, l = 0.05, ci.level = 0.95, qvalues = TRUE, plot.type = "main", FDR.level = 0.05, n.significant = NA)

Arguments

`pval`	Numerical vector of p-values (only necessary input).
`a`	Real value used in [-ln (1-pi)]^a (see details). If a == NA (default), then the value of a is automatically calculated as the greatest value such that the upper bound of the asymptotic standard deviation of the estimator of pi0 is smaller than the threshold l. If a >= 1, the value of a is used in [-ln (1-pi)]^a (see details). If a < 1, the identity function is used for transforming the p-values.
`l`	Threshold for the upper bound of the asymptotic standard deviation (only used if a == NA).
`ci.level`	Level for the confidence interval of pi0.
`qvalues`	Logical value for estimating the qvalues and the FDR. If qvalues = FALSE, only the proportion pi0 of true null hypotheses is estimated.
`plot.type`	If plot.type = "none", no graphic is displayed. If plot.type = "main", the estimated q-values versus the p-values are plotted together with the histogram of the p-values. If plot.type = "multiple", several graphics are displayed: 1. The histogram of the p-values 2. The estimated q-values versus the p-values 3. The number of significant tests versus each qvalue cutoff 4. The number of expected false positives versus the number of significant tests.
`FDR.level`	Level at which to control the FDR (only used if n.significant == NA).
`n.significant`	If specified, the FDR is estimated for the rejection region defined by the "n.significant" smallest p-values.

Details

The procedure LBE is based on the expectation of a particular transformation of the p-values leading to a straightforward estimation of the key quantity pi0 that is the proportion of true null hypotheses:

pi0(a)={(1/m)*∑_{i=1}^m[-ln(1-pi)]^a}/Γ(a+1), where a belongs to the interval [1;inf).

Value

A list containing:

`call`	Function call.
`FDR`	Level at which to control the FDR (if n.significant == NA) or estimated FDR (if n.significant != NA).
`pi0`	Estimated value of pi0, the proportion of true null hypotheses.
`pi0.ci`	Confidence interval for pi0.
`ci.level`	Level for the confidence interval of pi0.
`a`	Value used in [-ln (1-pi)]^a (see details).
`l`	Upper bound of the asymptotic standard deviation for pi0.
`qvalues`	Vector of the estimated q-values.
`pvalues`	Vector of the original p-values.
`significant`	Indicator of wether the null hypothesis is rejected.
`n.significant`	Number of rejected null hypotheses.

Note

LBE is an alternative method to the one proposed by Storey and Tibshirani (2003) for estimating the q-values, this latter method being implemented in the package qvalue.

Author(s)

Cyril Dalmasso

References

Dalmasso C, Broet P, Moreau T (2005). A simple procedure for estimating the false discovery rate. Bioinformatics. Bioinformatics, 21: 660 - 668.

Storey JD and Tibshirani R. (2003). Statistical significance for genome-wide studies. Proc Natl Acad Sci, 100, 9440-9445.

Examples

## start
data(hedenfalk.pval)
res=LBE(hedenfalk.pval)
data(golub.pval)
res=LBE(golub.pval)
## end

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(LBE)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/LBE/LBE.Rd_%03d_medium.png", width=480, height=480)
> ### Name: LBE
> ### Title: Estimation of the false discovery rate.
> ### Aliases: LBE
> ### Keywords: htest
> 
> ### ** Examples
> 
> ## start
> data(hedenfalk.pval)
> res=LBE(hedenfalk.pval)
> data(golub.pval)
> res=LBE(golub.pval)
> ## end
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>