aldex.glm {ALDEx2}R Documentation

calculate glm and Kruskal Wallis test statistics

Description

calculates expected values of the glm and Kruskal Wallis functions on the data returned by clr_function.r

Usage

aldex.glm(clr, conditions, useMC=FALSE)

Arguments

clr

clr is the data output of aldex.clr

conditions

a description of the data structure to be used for testing

useMC

use multicore by default (FALSE)

Details

An explicit example for two conditions is shown in the ‘Examples’ below.

Value

Outputs a dataframe with the following information:

kw.ep

a vector containing the expected P value of the Kruskal Wallis test for each feature

kw.eBH

a vector containing the expected value of the Benjamini Hochberg corrected P value for each feature

glm.ep

a vector containing the expected P value of the glm test for each feature

glm.eBH

a vector containing the expected value of the Benjamini Hochberg corrected P value for each feature

Author(s)

Arianne Albert

References

Please use the citation given by citation(package="ALDEx").

See Also

aldex.clr, aldex.ttest, aldex.effect, selex

Examples

    # x is the output of the \code{x <- aldex.clr(data, mc.samples)} function
    # conditions is a description of the data
    # for the selex dataset, conditions <- c(rep("N", 7), rep("S", 7))
    data(selex)
    #subset for efficiency
    selex <- selex[1201:1600,]
    conds <- c(rep("NS", 7), rep("S", 7))
    x <- aldex.clr(selex, conds, mc.samples=1, denom="all")
    glm.test <- aldex.glm(x, conds)

[Package ALDEx2 version 1.12.0 Index]