Learn R Programming

WGCNA (version 1.61)

qvalue: Estimate the q-values for a given set of p-values

Description

Estimate the q-values for a given set of p-values. The q-value of a test measures the proportion of false positives incurred (called the false discovery rate) when that particular test is called significant.

Usage

qvalue(p, lambda=seq(0,0.90,0.05), pi0.method="smoother", fdr.level=NULL, robust=FALSE,
  smooth.df=3, smooth.log.pi0=FALSE)

Arguments

p

A vector of p-values (only necessary input)

lambda

The value of the tuning parameter to estimate \(\pi_0\). Must be in [0,1). Optional, see Storey (2002).

pi0.method

Either "smoother" or "bootstrap"; the method for automatically choosing tuning parameter in the estimation of \(\pi_0\), the proportion of true null hypotheses

fdr.level

A level at which to control the FDR. Must be in (0,1]. Optional; if this is selected, a vector of TRUE and FALSE is returned that specifies whether each q-value is less than fdr.level or not.

robust

An indicator of whether it is desired to make the estimate more robust for small p-values and a direct finite sample estimate of pFDR. Optional.

smooth.df

Number of degrees-of-freedom to use when estimating \(\pi_0\) with a smoother. Optional.

smooth.log.pi0

If TRUE and pi0.method = "smoother", \(\pi_0\) will be estimated by applying a smoother to a scatterplot of \(log\) \(\pi_0\) estimates against the tuning parameter \(\lambda\). Optional.

Value

A list containing:

call

function call

pi0

an estimate of the proportion of null p-values

qvalues

a vector of the estimated q-values (the main quantity of interest)

pvalues

a vector of the original p-values

significant

if fdr.level is specified, and indicator of whether the q-value fell below fdr.level (taking all such q-values to be significant controls FDR at level fdr.level)

Details

If no options are selected, then the method used to estimate \(\pi_0\) is the smoother method described in Storey and Tibshirani (2003). The bootstrap method is described in Storey, Taylor & Siegmund (2004).

References

Storey JD. (2002) A direct approach to false discovery rates. Journal of the Royal Statistical Society, Series B, 64: 479-498.

Storey JD and Tibshirani R. (2003) Statistical significance for genome-wide experiments. Proceedings of the National Academy of Sciences, 100: 9440-9445.

Storey JD. (2003) The positive false discovery rate: A Bayesian interpretation and the q-value. Annals of Statistics, 31: 2013-2035.

Storey JD, Taylor JE, and Siegmund D. (2004) Strong control, conservative point estimation, and simultaneous conservative consistency of false discovery rates: A unified approach. Journal of the Royal Statistical Society, Series B, 66: 187-205.