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benchdamic
This package is for version 3.21 of Bioconductor; for the stable, up-to-date release version, see benchdamic.
Benchmark of differential abundance methods on microbiome data
Bioconductor version: 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 iD ORCID: 0000-0002-3056-518X , Chiara Romualdi [aut] ORCID iD ORCID: 0000-0003-4792-9047 , Davide Risso [aut] ORCID iD ORCID: 0000-0001-8508-5012 , Nicola Vitulo [aut] ORCID iD ORCID: 0000-0002-9571-0747
Maintainer: Matteo Calgaro <mcalgaro93 at gmail.com>
citation("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.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("benchdamic")
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Follow Installation instructions to use this package in your R session.