| aldex.glm {ALDEx2} | R Documentation |
calculates expected values of the glm and Kruskal Wallis functions on the data returned by clr_function.r
aldex.glm(clr, conditions, useMC=FALSE)
clr |
|
conditions |
a description of the data structure to be used for testing |
useMC |
use multicore by default (FALSE) |
An explicit example for two conditions is shown in the ‘Examples’ below.
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 |
Arianne Albert
Please use the citation given by citation(package="ALDEx").
aldex.clr,
aldex.ttest,
aldex.effect,
selex
# 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)