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This is the development version of dar; to use it, please install the devel version of Bioconductor.

Differential Abundance Analysis by Consensus

Bioconductor version: Development (3.19)

Differential abundance testing in microbiome data challenges both parametric and non-parametric statistical methods, due to its sparsity, high variability and compositional nature. Microbiome-specific statistical methods often assume classical distribution models or take into account compositional specifics. These produce results that range within the specificity vs sensitivity space in such a way that type I and type II error that are difficult to ascertain in real microbiome data when a single method is used. Recently, a consensus approach based on multiple differential abundance (DA) methods was recently suggested in order to increase robustness. With dar, you can use dplyr-like pipeable sequences of DA methods and then apply different consensus strategies. In this way we can obtain more reliable results in a fast, consistent and reproducible way.

Author: Francesc Catala-Moll [aut, cre]

Maintainer: Francesc Catala-Moll <fcatala at>

Citation (from within R, enter citation("dar")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


Reference Manual PDF


biocViews Metagenomics, Microbiome, MultipleComparison, Normalization, Sequencing, Software
Version 0.99.11
In Bioconductor since BioC 3.19 (R-4.4)
License MIT + file LICENSE
Depends R (>= 4.4.0)
Imports cli, ComplexHeatmap, crayon, dplyr, generics, ggplot2, glue, gplots, heatmaply, magrittr, methods, mia, phyloseq, purrr, readr, rlang (>= 0.4.11), scales, stringr, tibble, tidyr, UpSetR, waldo
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Suggests ALDEx2, ANCOMBC, apeglm, ashr, Biobase, corncob, covr, DESeq2, devtools, furrr, future, knitr, lefser, limma, Maaslin2, metagenomeSeq, microbiome, rmarkdown, roxygen2, roxyglobals, roxytest, rstatix, SummarizedExperiment, testthat (>= 3.0.0)
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