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 1.64.0 Index]