ALDEx2 (version 1.4.0)

aldex.effect: calculate effect sizes and differences between conditions

Description

determines the median clr abundance of the feature in all samples and in groups determines the median difference between the two groups determines the median variation within each two group determines the effect size, which is the median of the ratio of the between group difference and the larger of the variance within groups

Usage

aldex.effect(clr, conditions, verbose = TRUE, include.sample.summary = FALSE, useMC=FALSE)

Arguments

clr

clr is the data output of aldex.clr

conditions

a description of the data structure to be used for testing

verbose

Print diagnostic information while running. Useful only for debugging if fails on large datasets

include.sample.summary

include median clr values for each sample, defaults to FALSE

useMC

use multicore by default (FALSE)

Value

returns a dataframe with the following information:

rab.all

a vector containing the median clr value for each feature

rab.win.conditionA

a vector containing the median clr value for each feature in condition A

rab.win.conditionB

a vector containing the median clr value for each feature in condition B

diff.btw

a vector containing the per-feature median difference between condition A and B

diff.btw

a vector containing the per-feature maximum median difference between Dirichlet instances within conditions

effect

a vector containing the per-feature effect size

overlap

a vector containing the per-feature proportion of effect size that is 0 or less

Details

An explicit example for two conditions is shown in the `Examples' below.

References

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

See Also

aldex.clr, aldex.ttest, aldex.glm, selex

Examples

    # x is the output of the \code{x <- 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)
    x <- aldex.clr(selex, mc.samples=2)
    conditions <- c(rep("N", 7), rep("S", 7))
    effect.test <- aldex.effect(x, conditions)