dar
Differential Abundance Analysis by Consensus
DOI: 10.18129/B9.bioc.dar
Bioconductor version: Release (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("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 | ||
| NEWS | Text | |
| LICENSE | Text |
Details
| biocViews | Metagenomics, Microbiome, MultipleComparison, Normalization, Sequencing, Software |
| Version | 1.0.0 |
| In Bioconductor since | BioC 3.19 (R-4.4) (< 6 months) |
| 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) |
| 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_1.0.0.tar.gz |
| Windows Binary (x86_64) | dar_1.0.0.zip |
| macOS Binary (x86_64) | dar_1.0.0.tgz |
| macOS Binary (arm64) | dar_1.0.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/dar |
| Source Repository (Developer Access) | git clone [email protected]:packages/dar |
| Bioc Package Browser | https://code.bioconductor.org/browse/dar/ |
| Package Short Url | https://bioconductor.org/packages/dar/ |
| Package Downloads Report | Download Stats |