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dar

This is the released version of dar; for the devel version, see dar.

Differential Abundance Analysis by Consensus


Bioconductor version: Release (3.20)

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 irsicaixa.es>

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

Installation

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


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("dar")

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

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("dar")
Data Import HTML R Script
Filtering and Subsetting HTML R Script
Introduction to dar HTML R Script
Reproducibility in Microbiome Data Analysis HTML R Script
Workflow with real data HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews Metagenomics, Microbiome, MultipleComparison, Normalization, Sequencing, Software
Version 1.2.0
In Bioconductor since BioC 3.19 (R-4.4) (0.5 years)
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
System Requirements
URL https://github.com/MicrobialGenomics-IrsicaixaOrg/dar https://microbialgenomics-irsicaixaorg.github.io/dar/
Bug Reports https://github.com/MicrobialGenomics-IrsicaixaOrg/dar/issues
See More
Suggests ALDEx2, ANCOMBC, apeglm, ashr, Biobase, corncob, covr, DESeq2, devtools, furrr, future, knitr, lefser, limma, Maaslin2, metagenomeSeq, microbiome, rmarkdown, roxygen2, roxyglobals, roxytest, rstatix, SummarizedExperiment, TreeSummarizedExperiment, testthat (>= 3.0.0)
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package dar_1.2.0.tar.gz
Windows Binary (x86_64) dar_1.2.0.zip
macOS Binary (x86_64) dar_1.2.0.tgz
macOS Binary (arm64) dar_1.2.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/dar
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/dar
Bioc Package Browser https://code.bioconductor.org/browse/dar/
Package Short Url https://bioconductor.org/packages/dar/
Package Downloads Report Download Stats