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ALDEx2 (version 1.4.0)

Analysis of differential abundance taking sample variation into account

Description

A differential abundance analysis for the comparison of two or more conditions. For example, single-organism and meta-RNA-seq high-throughput sequencing assays, or of selected and unselected values from in-vitro sequence selections. Uses a Dirichlet-multinomial model to infer abundance from counts, that has been optimized for three or more experimental replicates. Infers sampling variation and calculates the expected false discovery rate given the biological and sampling variation using the Wilcox rank test or Welches t-test (aldex.ttest) or the glm and Kruskal Wallis tests (aldex.glm). Reports both P and fdr values calculated by the Benjamini Hochberg correction.

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Version

Version

1.4.0

License

file LICENSE

Maintainer

Last Published

February 15th, 2017

Functions in ALDEx2 (1.4.0)

getFeatures

getFeatures
numFeatures

numFeatures
getSampleIDs

getSampleIDs
aldex.plot

Plot an aldex Object
aldex.clr

Compute an aldex.clr Object
getReads

getReads
numMCInstances

numMCInstances
aldex.corr

calculate Pearson's Product moment and Spearman's rank correlations
ALDEx2m-package

Analysis of differential abundance taking sample variation into account
aldex.ttest

calculate Welch's t-test and Wilcoxon test statistics
aldex

Compute an aldex Object
aldex.effect

calculate effect sizes and differences between conditions
aldex.clr-class

The aldex.clr class
getFeatureNames

getFeatureNames
selex

Selection-based differential sequence variant abundance dataset
getMonteCarloReplicate

getMonteCarloReplicate
numConditions

numConditions
aldex.glm

calculate glm and Kruskal Wallis test statistics
getMonteCarloInstances

getMonteCarloInstances