Package: ALDEx2 1.39.0

Greg Gloor

ALDEx2: Analysis Of Differential Abundance Taking Sample and Scale Variation Into Account

A differential abundance analysis for the comparison of two or more conditions. Useful for analyzing data from standard RNA-seq or meta-RNA-seq assays as well as selected and unselected values from in-vitro sequence selections. Uses a Dirichlet-multinomial model to infer abundance from counts, optimized for three or more experimental replicates. The method infers biological and sampling variation to calculate the expected false discovery rate, given the variation, based on a Wilcoxon Rank Sum test and Welch's t-test (via aldex.ttest), a Kruskal-Wallis test (via aldex.kw), a generalized linear model (via aldex.glm), or a correlation test (via aldex.corr). All tests report predicted p-values and posterior Benjamini-Hochberg corrected p-values. ALDEx2 also calculates expected standardized effect sizes for paired or unpaired study designs. ALDEx2 can now be used to estimate the effect of scale on the results and report on the scale-dependent robustness of results.

Authors:Greg Gloor, Andrew Fernandes, Jean Macklaim, Arianne Albert, Matt Links, Thomas Quinn, Jia Rong Wu, Ruth Grace Wong, Brandon Lieng, Michelle Nixon

ALDEx2_1.39.0.tar.gz
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ALDEx2.pdf |ALDEx2.html
ALDEx2/json (API)
NEWS

# Install 'ALDEx2' in R:
install.packages('ALDEx2', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ggloor/aldex_bioc/issues

Datasets:
  • selex - Selection-based differential sequence variant abundance dataset
  • synth2 - Synthetic asymmetric dataset

On BioConductor:ALDEx2-1.37.0(bioc 3.20)ALDEx2-1.36.0(bioc 3.19)

differentialexpressionrnaseqtranscriptomicsgeneexpressiondnaseqchipseqbayesiansequencingsoftwaremicrobiomemetagenomicsimmunooncologyscale simulationposterior p-value

9.77 score 27 stars 4 packages 426 scripts 1.9k downloads 34 exports 58 dependencies

Last updated 23 days agofrom:f7a601796f. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winNOTEOct 30 2024
R-4.5-linuxNOTEOct 30 2024
R-4.4-winNOTEOct 30 2024
R-4.4-macNOTEOct 30 2024
R-4.3-winOKOct 30 2024
R-4.3-macOKOct 30 2024

Exports:aldexaldex.clraldex.clr.functionaldex.corraldex.effectaldex.expectedDistancealdex.glmaldex.glm.effectaldex.glm.plotaldex.kwaldex.makeScaleMatrixaldex.plotaldex.plotFeaturealdex.senAnalysisaldex.set.modealdex.ttestgetConditionsgetDenomgetDirichletInstancesgetDirichletReplicategetDirichletSamplegetFeatureNamesgetFeaturesgetMonteCarloInstancesgetMonteCarloReplicategetMonteCarloSamplegetReadsgetSampleIDsgetScaleSamplesinterpretGammanumConditionsnumFeaturesnumMCInstancesplotGamma

Dependencies:abindaskpassBHBiobaseBiocGenericsBiocParallelcodetoolscpp11crayoncurlDelayedArraydeldirdirectlabelsformatRfutile.loggerfutile.optionsGenomeInfoDbGenomeInfoDbDataGenomicRangeshttrinterpIRangesjpegjsonlitelambda.rlatticelatticeExtraMASSMatrixMatrixGenericsmatrixStatsmimemulttestNADAopensslpngquadprogR6RColorBrewerRcppRcppArmadilloRcppEigenRcppGSLRcppParallelRcppZigguratRfastS4ArraysS4VectorssnowSparseArraySummarizedExperimentsurvivalsystruncnormUCSC.utilsXVectorzCompositionszlibbioc

ANOVA-Like Differential Expression tool for high throughput sequencing data

Rendered fromALDEx2_vignette.Rmdusingknitr::rmarkdownon Oct 30 2024.

Last update: 2023-10-05
Started: 2018-07-27

Incorporating Scale Uncertainty into ALDEx2

Rendered fromscaleSim_vignette.Rmdusingknitr::rmarkdownon Oct 30 2024.

Last update: 2023-10-01
Started: 2023-04-26

Readme and manuals

Help Manual

Help pageTopics
Analysis of differential abundance taking sample variation into accountALDEx2m-package ALDEx2m
Compute an 'aldex' Objectaldex
The aldex.clr classaldex.clr-class
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 aldex.clr,data.frame-method aldex.clr,matrix-method aldex.clr,RangedSummarizedExperiment-method aldex.clr.function
Calculate correlation with a continuous variablealdex.corr
Calculate effect sizes and differences between conditionsaldex.effect
Calculate the expected values of distances between samples, given an 'aldex' Objectaldex.expectedDistance
Calculate glm test statistics using a 'model.matrix'aldex.glm
calculate effect sizes and differences between all contrasts for the aldex.glm model matrixaldex.glm.effect
Plot an 'aldex' Objectaldex.glm.plot
Calculate the Kruskal-Wallis test and glm statisticsaldex.kw
Generate a differential scale matrix by groupaldex.makeScaleMatrix
Plot an 'aldex' Objectaldex.plot
Show dispersion of the expected values returned by 'aldex.effect'aldex.plotFeature
Sensitivity analysis using scale simulationaldex.senAnalysis
identify set of denominator features for log-ratio calculationaldex.set.mode
Calculate Wilcoxon Rank Sum test and Welch's t-test statisticsaldex.ttest
getConditionsgetConditions getConditions,aldex.clr-method
getDenomgetDenom getDenom,aldex.clr-method
getDirichletInstancesgetDirichletInstances getDirichletInstances,aldex.clr-method
getDirichletReplicategetDirichletReplicate getDirichletReplicate,aldex.clr,numeric-method
getDirichletSamplegetDirichletSample getDirichletSample,aldex.clr,numeric-method
getFeatureNamesgetFeatureNames getFeatureNames,aldex.clr-method
getFeaturesgetFeatures getFeatures,aldex.clr-method
getMonteCarloInstancesgetMonteCarloInstances getMonteCarloInstances,aldex.clr-method
getMonteCarloReplicategetMonteCarloReplicate getMonteCarloReplicate,aldex.clr,numeric-method
getMonteCarloSamplegetMonteCarloSample getMonteCarloSample,aldex.clr,numeric-method
getReadsgetReads getReads,aldex.clr-method
getSampleIDsgetSampleIDs getSampleIDs,aldex.clr-method
getScaleSamplesgetScaleSamples getScaleSamples,aldex.clr-method
Interpret the scale model implied by a certain level of gamma or scale modelinterpretGamma
numConditionsnumConditions numConditions,aldex.clr-method
numFeaturesnumFeatures numFeatures,aldex.clr-method
numMCInstancesnumMCInstances numMCInstances,aldex.clr-method
Create gamma diagram for scale simulation sensitivity resultplotGamma
Selection-based differential sequence variant abundance datasetselex
Synthetic asymmetric datasetsynth2