EMA (version 1.4.7)

multiple.correction: Multiple testing correction

Description

Given a set of p-values, returns p-values adjusted using one of several methods.

Usage

multiple.correction(pval, typeFDR, q)

Arguments

pval

Vector of pvalues.

typeFDR

The correction method.

q

The error rate to use for the Two-stages procedure (FDR-TST).

Value

A vector of adjusted pvalues.

Details

The multiple correction methods include Bonferroni correction ("FWER"), Benjamini-Hochberg standard false discovery rate correction ("FDR-BH"), Benjamini-Hochberg Adaptive Procedure ("FDR-TST") and the Qvalue procedure (Storey).

References

- Benjamini Y and Hochberg Y. (1995) Controlling the false discovery rate: A practical and powerful approach to multiple testing. . Journal of the Royal Statistical Society, Series B, 57: 289-300. - Storey JD. (2002) A direct approach to false discovery rates. Journal of the Royal Statistical Society, Series B, 64: 479-498. - Benjamini Y., Kenigsberg E., Reiner A., Yekutieli D (2005). FDR adjustments of Microarray Experiments.

See Also

p.adjust

Examples

# NOT RUN {
## load data
data(marty)

## filtering data
marty <- expFilter(marty, threshold=3.5, graph=FALSE)


##Class label 0/1
marty.type.num <- ifelse(marty.type.cl=="Her2+",0,1)

##Example dataset
example.subset<-marty[1:100,]

## run differential analysis Basal vs HER2+
out <- runTtest(example.subset, labels=marty.type.num, typeFDR="FDR-BH")
## OR :
out2 <- multiple.correction(out$RawpValue, typeFDR="FDR-BH")
# }
# NOT RUN {

# }