EMA (version 1.4.4)

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")
# ## End(Not run)