BonEV-package: BonEV: An Improved Multiple Testing Procedure for Controlling...
In ur-ctsi/BonEV: An Improved Multiple Testing Procedure for Controlling False Discovery Rates
Description
Details
Author(s)
See Also
Examples
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
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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$Bon_EV_adjp <= 0.05)
ur-ctsi/BonEV documentation built on Nov. 5, 2019, 11:06 a.m.
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Description Details Author(s) See Also Examples
Description
BonEV is an improved multiple testing procedure for controlling false discovery rates which is developed based on the Bonferroni procedure with integrated estimates from the Benjamini-Hochberg procedure and the Storey's q-value procedure. It controls false discovery rates through controlling the expected number of false discoveries.
Details
| Package: | BonEV |
| Type: | Package |
| Version: | 1.0.0 |
| Date: | 2015-02-10 |
| Depends: | R (>= 3.2.0), qvalue |
| License: | GPL (>= 2) |
Author(s)
Dongmei Li Maintainer: Dongmei Li <dongmei_li@urmc.rochester.edu>
See Also
The Bon_EV function defined in this package.
The qvalue package.
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | library(qvalue)
data(hedenfalk)
summary(hedenfalk)
pvalues <- hedenfalk$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)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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