BonEV (version 1.0)

Bon_EV: Bon_EV: A R Function of Improved Multiple Testing Procedure for Controlling False Discovery Rates

Description

Bon_EV is an improved multiple testing procedure for controlling false discovery rates which is developed based on the Bonferroni procedure with integrated estimates from the Benjamini-Hochberg procedure and the Storey's q-value procedure. It controls false discovery rates through controlling the expected number of false discoveries.

Usage

Bon_EV(pvalue, alpha)

Arguments

pvalue

The input data is a vector of P-values ranged from 0 to 1

alpha

The alpha is the level of false discovery rates (FDR) to control for

Value

Bon_EV produces a named list with the following components:

raw_P_value

Vector of raw P-values

BH_adjp

Adjusted P-values from the Benjamini-Hochberg procedure

Storey_adjp

Adjusted P-values from the Storey's q-value procedure

Bon_EV_adjp

Adjusted P-values from the Bon-EV multiple testing procedure

Details

Bon_EV is a function for getting adjusted P-values with FDR controlled at level alpha.

See Also

The qvalue package.

Examples

library(qvalue)
data(hedenfalk)
summary(hedenfalk)
pvalues <- hedenfalk$p
adjp <- Bon_EV(pvalues, 0.05)
summary(adjp)
sum(adjp$Bon_EV_adjp <= 0.05)