Analysis Of Differential Abundance Taking Sample and Scale
Variation Into Account
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Documentation for package ‘ALDEx2’ version 1.41.0
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 |