| Type: | Package |
| Title: | An Improved Multiple Testing Procedure for Controlling False Discovery Rates |
| Version: | 1.0 |
| Date: | 2016-02-10 |
| Author: | Dongmei Li |
| Maintainer: | Dongmei Li <dongmei_li@urmc.rochester.edu> |
| Depends: | R (≥ 3.2.0), qvalue |
| Description: | 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. |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Packaged: | 2016-02-12 15:57:59 UTC; dli3 |
| Repository: | CRAN |
| Date/Publication: | 2016-02-13 00:59:51 |
BonEV: An Improved Multiple Testing Procedure for Controlling False Discovery Rates
Description
BonEV 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.
Details
| Package: | BonEV |
| Type: | Package |
| Version: | 1.0.0 |
| Date: | 2015-02-10 |
| Depends: | R (>= 3.2.0), qvalue |
| License: | GPL (>= 2) |
Author(s)
Dongmei Li Maintainer: Dongmei Li <dongmei_li@urmc.rochester.edu>
See Also
The Bon_EV function defined in this package.
The qvalue package.
Examples
library(qvalue)
data(hedenfalk)
summary(hedenfalk)
pvalues <- hedenfalk$p
adjp <- Bon_EV(pvalues, 0.05)
summary(adjp)
results <- cbind(adjp$raw_P_value, adjp$BH_adjp, adjp$Storey_adjp, adjp$Bon_EV_adjp)
results
##Compare with Benjamini-Hochberg and Storey's q-value procedures
sum(adjp$raw_P_value <= 0.05)
sum(adjp$BH_adjp <= 0.05)
sum(adjp$Storey_adjp <= 0.05)
sum(adjp$Bon_EV_adjp <= 0.05)
Bon_EV: A R Function of Improved Multiple Testing Procedure for Controlling False Discovery Rates
Description
Bon_EV is an improved multiple testing procedure for controlling false discovery rates which is developed based on the Bonferroni procedure with integrated estimates from the Benjamini-Hochberg procedure and the Storey's q-value procedure. It controls false discovery rates through controlling the expected number of false discoveries.
Usage
Bon_EV(pvalue, alpha)
Arguments
pvalue |
The input data is a vector of P-values ranged from 0 to 1 |
alpha |
The alpha is the level of false discovery rates (FDR) to control for |
Details
Bon_EV is a function for getting adjusted P-values with FDR controlled at level alpha.
Value
Bon_EV produces a named list with the following components:
raw_P_value |
Vector of raw P-values |
BH_adjp |
Adjusted P-values from the Benjamini-Hochberg procedure |
Storey_adjp |
Adjusted P-values from the Storey's q-value procedure |
Bon_EV_adjp |
Adjusted P-values from the Bon-EV multiple testing procedure |
Author(s)
Dongmei Li
See Also
The qvalue package.
Examples
library(qvalue)
data(hedenfalk)
summary(hedenfalk)
pvalues <- hedenfalk$p
adjp <- Bon_EV(pvalues, 0.05)
summary(adjp)
sum(adjp$Bon_EV_adjp <= 0.05)