# Analysis Of Differential Abundance Taking Sample and Scale Variation Into Account

## Documentation for package ‘ALDEx2’ version 1.45.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

ALDEx2m-package | Analysis of differential abundance taking sample variation into account
aldex | Compute an 'aldex' Object
aldex.clr | Compute an 'aldex.clr' Object Generate Monte Carlo samples of the Dirichlet distribution for each sample. Convert each instance using a centered log-ratio transform. This is the input for all further analyses.
aldex.clr-class | The aldex.clr class
aldex.clr-method | Compute an 'aldex.clr' Object Generate Monte Carlo samples of the Dirichlet distribution for each sample. Convert each instance using a centered log-ratio transform. This is the input for all further analyses.
aldex.clr.function | Compute an 'aldex.clr' Object Generate Monte Carlo samples of the Dirichlet distribution for each sample. Convert each instance using a centered log-ratio transform. This is the input for all further analyses.
aldex.corr | Calculate correlation with a continuous variable
aldex.effect | Calculate effect sizes and differences between conditions
aldex.expectedDistance | Calculate the expected values of distances between samples, given an 'aldex' Object
aldex.glm | Calculate glm test statistics using a 'model.matrix'
aldex.glm.effect | calculate effect sizes and differences between all contrasts for the aldex.glm model matrix
aldex.glm.plot | Plot an 'aldex' Object
aldex.kw | Calculate the Kruskal-Wallis test and glm statistics
aldex.makeScaleMatrix | Generate a differential scale matrix by group
aldex.plot | Plot an 'aldex' Object
aldex.plotFeature | Show dispersion of the expected values returned by 'aldex.effect'
aldex.senAnalysis | Sensitivity analysis using scale simulation
aldex.set.mode | identify set of denominator features for log-ratio calculation
aldex.ttest | Calculate Wilcoxon Rank Sum test and Welch's t-test statistics
ALDEx2m | Analysis of differential abundance taking sample variation into account
getConditions | getConditions
getConditions-method | getConditions
getDenom | getDenom
getDenom-method | getDenom
getDirichletInstances | getDirichletInstances
getDirichletInstances-method | getDirichletInstances
getDirichletReplicate | getDirichletReplicate
getDirichletReplicate-method | getDirichletReplicate
getDirichletSample | getDirichletSample
getDirichletSample-method | getDirichletSample
getFeatureNames | getFeatureNames
getFeatureNames-method | getFeatureNames
getFeatures | getFeatures
getFeatures-method | getFeatures
getMonteCarloInstances | getMonteCarloInstances
getMonteCarloInstances-method | getMonteCarloInstances
getMonteCarloReplicate | getMonteCarloReplicate
getMonteCarloReplicate-method | getMonteCarloReplicate
getMonteCarloSample | getMonteCarloSample
getMonteCarloSample-method | getMonteCarloSample
getReads | getReads
getReads-method | getReads
getSampleIDs | getSampleIDs
getSampleIDs-method | getSampleIDs
getScaleSamples | getScaleSamples
getScaleSamples-method | getScaleSamples
interpretGamma | Interpret the scale model implied by a certain level of gamma or scale model
numConditions | numConditions
numConditions-method | numConditions
numFeatures | numFeatures
numFeatures-method | numFeatures
numMCInstances | numMCInstances
numMCInstances-method | numMCInstances
plotGamma | Create gamma diagram for scale simulation sensitivity result
selex | Selection-based differential sequence variant abundance dataset
synth2 | Synthetic asymmetric dataset