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DOI: 10.18129/B9.bioc.ALDEx2    

This is the development version of ALDEx2; for the stable release version, see ALDEx2.

Analysis Of Differential Abundance Taking Sample Variation Into Account

Bioconductor version: Development (3.6)

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 Wilcox rank test or Welch t-test (via aldex.ttest), or a glm and Kruskal-Wallis test (via aldex.glm). Reports p-values and Benjamini-Hochberg corrected p-values.

Author: Greg Gloor, Ruth Grace Wong, Andrew Fernandes, Arianne Albert, Matt Links, Thomas Quinn, Jia Rong Wu

Maintainer: Greg Gloor <ggloor at>

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PDF R Script An R Package for determining differential abundance in high throughput sequencing experiments
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biocViews Bayesian, ChIPSeq, DNASeq, DifferentialExpression, GeneExpression, Metagenomics, Microbiome, RNASeq, Sequencing, Software
Version 1.9.1
In Bioconductor since BioC 3.0 (R-3.1) (3 years)
License file LICENSE
Depends methods, stats
Imports BiocParallel, GenomicRanges, IRanges, S4Vectors, SummarizedExperiment, multtest
Suggests testthat
Depends On Me
Imports Me
Suggests Me
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