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.

`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]