qvalue.cal: Computation of the q-value
In siggenes: Multiple Testing using SAM and Efron's Empirical Bayes Approaches

Description Usage Arguments Details Value Author(s) References See Also Examples

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

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

`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.

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.

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

Holger Schwender, holger.schw@gmx.de

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.

pi0.est,SAM-class,sam

## 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)