Description Usage Arguments Details Value Author(s) See Also Examples
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.
1 | 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.
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