dar

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 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")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

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

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	Metagenomics, Microbiome, MultipleComparison, Normalization, Sequencing, Software
Version	0.99.13
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
System Requirements
URL	https://github.com/MicrobialGenomics-IrsicaixaOrg/dar https://microbialgenomics-irsicaixaorg.github.io/dar/
Bug Reports	https://github.com/MicrobialGenomics-IrsicaixaOrg/dar/issues

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)
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report	Build Report

Package Archives

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

Source Package	dar_0.99.13.tar.gz
Windows Binary	dar_0.99.13.zip
macOS Binary (x86_64)	dar_0.99.13.tgz
macOS Binary (arm64)	dar_0.99.13.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