BH: Benjamini-Hochberg (BH) multiple testing procedure

In sgof: Multiple Hypothesis Testing

Benjamini-Hochberg (BH) multiple testing procedure

Description

Performs the Benjamini-Hochberg FDR-controlling method for multiple hypothesis testing.

Usage

BH(u, alpha = 0.05)

Arguments

u	A (non-empty) numeric vector of p-values.
alpha	Numeric value. The significance level of the test.

Details

The function BH allows for the application of the Benjamini and Hochberg (1995) false discovery rate controlling procedure. The false discovery rate is estimated by the simple method proposed by: Dalmasso, Broet, Moreau (2005), by taking n=1 in their formula.

Value

A list containing the following values:

Rejections	The number of effects declared by the BH procedure.
FDR	The estimated false discovery rate.
Adjusted.pvalues	The adjusted p-values.
data	The original p-values.
alpha	The specified significance level for the test.
call	The matched call.

Author(s)

Irene Castro Conde and Jacobo de Uña Álvarez

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 (Methodological) 57, 289–300.

Dalmasso C, Broet P and Moreau T (2005). A simple procedure for estimating the false discovery rate. Bioinformatics 21:660–668

See Also

plot.BH,summary.BH

Examples

res<-BH(Hedenfalk$x)
summary(res)   #number of rejected nulls, estimated FDR
plot(res)   #adjusted p-values

sgof documentation built on Sept. 8, 2023, 5:34 p.m.