This is the released version of benchdamic; for the devel version, see benchdamic.
Benchmark of differential abundance methods on microbiome dataBioconductor version: Release (3.21)
Starting from a microbiome dataset (16S or WMS with absolute count values) it is possible to perform several analysis to assess the performances of many differential abundance detection methods. A basic and standardized version of the main differential abundance analysis methods is supplied but the user can also add his method to the benchmark. The analyses focus on 4 main aspects: i) the goodness of fit of each method's distributional assumptions on the observed count data, ii) the ability to control the false discovery rate, iii) the within and between method concordances, iv) the truthfulness of the findings if any apriori knowledge is given. Several graphical functions are available for result visualization.
Author: Matteo Calgaro [aut, cre] ORCID: 0000-0002-3056-518X , Chiara Romualdi [aut] ORCID: 0000-0003-4792-9047 , Davide Risso [aut] ORCID: 0000-0001-8508-5012 , Nicola Vitulo [aut] ORCID: 0000-0002-9571-0747
Maintainer: Matteo Calgaro <mcalgaro93 at gmail.com>
Citation (from within R, entercitation("benchdamic")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("benchdamic")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("benchdamic")Follow Installation instructions to use this package in your R session.
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