qvalue.cal {siggenes}R Documentation

Computation of the q-value

Description

Computes the q-values of a given set of p-values.

Usage

  qvalue.cal(p, p0, version = 1)

Arguments

p a numeric vector containing the p-values
p0 a numeric value specifying the prior probability that a gene is not differentially expressed
version If version=2, the original version of the q-value, i.e. min{pFDR}, will be computed. if version=1, min{FDR} will be used in the computation of the q-value

Details

Using version=1 in qvalue.cal corresponds to setting robust=FALSE in the function qvalue of John Storey's R package qvalue, while version=2 corresponds to robust=TRUE.

Value

a vector of the same length as p containing the q-values corresponding to the p-values in p

Author(s)

Holger Schwender, holger.schw@gmx.de

References

Storey, J.D. (2003). The positive False Discovery Rate: A Bayesian Interpretation and the q-value. Annals of Statistics, 31, 2013-2035.

Storey, J.D., and Tibshirani, R. (2003). Statistical Significance for Genome-wide Studies. PNAS, 100, 9440-9445.

See Also

pi0.est,SAM-class,sam

Examples

## Not run: 
  # Load the package multtest and the data of Golub et al. (1999)
  # contained in multtest.
  library(multtest)
  data(golub)

  # Perform a SAM analysis.
  sam.out<-sam(golub,golub.cl,B=100,rand=123)

  # Estimate the prior probability that a gene is not significant.
  pi0<-pi0.est(sam.out@p.value)$p0
  
  # Compute the q-values of the genes.
  q.value<-qvalue.cal(sam.out@p.value,pi0)
## End(Not run)

[Package siggenes version 1.4.0 Index]