Bon_EV {BonEV} | R Documentation |
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.
Bon_EV(pvalue, alpha)
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 |
Bon_EV is a function for getting adjusted P-values with FDR controlled at level alpha.
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 |
Dongmei Li
The qvalue package.
library(qvalue)
data(hedenfalk)
summary(hedenfalk)
pvalues <- hedenfalk$p
adjp <- Bon_EV(pvalues, 0.05)
summary(adjp)
sum(adjp$Bon_EV_adjp <= 0.05)