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Alpha Correction R Package

`library(alpha-correction-bh)`

Introduction

This package provides functions for calculating alpha corrections for a list of p-values according to the Benjamini-Hochberg alpha correction.

Reference: Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: series B (Methodological), 57(1), 289-300.

For a sorted list containing m p-values indexed from 1 to m, the alpha for each p-value p is computed as:

                      alpha(i) = (p_value(i)/m)Q

where:

i is the index of the p-value in list l (1 to m),
p_value(i) is the p_value at index i, and
Q is the false discovery rate, which is 0.05 by default.

Installation

Install the package using dev-tools directly from github or from cran.

devtools::install_github('pcla-code/alpha.correction.bh')

Dependencies

This library uses knitr to render tables.

Usage

Import the package:

library(alpha-correction-bh)

library(knitr)

And call the get_alphas_bh function, passing your p_values and, optionally, Q:

get_alphas_bh(p_values, Q)

Use this function to calculate corrected values for a list of p-values and a given false discovery rate Q.

If you do not provide Q, a default value of 0.05 will be used.

Output Options

You can customize the output of the function using the following two options:

output - valid values are:
- print - print the data frame to the console only
- data_frame - return the data frame only
- both - print the data frame to the console and return it. This is the default behavior.
include_is_significant_column - valid values are:
- TRUE - The is significant? column is included. This is the default behavior.
- FALSE - The is significant? column is not included.

Example 1:

get_alphas_bh(list(0.08,0.01,0.039))

Output:

p-value	alpha	is significant?
0.08	0.05	NO
0.01	0.017	YES
0.039	0.033	NO

Example 2:

get_alphas_bh(list(0.08,0.01,0.039), .07)

Output:

p-value	alpha	is significant?
0.08	0.07	NO
0.01	0.023	YES
0.039	0.047	YES

Documentation

To read the documentation of the function, execute the following in R:

?get_alphas_bh

You can also read the vignette here.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.