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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "dar" in publications use:'
type: software
license: MIT
title: 'dar: Differential Abundance Analysis by Consensus'
version: 1.1.1
doi: 10.32614/CRAN.package.dar
abstract: 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.
authors:
- family-names: Catala-Moll
  given-names: Francesc
  email: fcatala@irsicaixa.es
  orcid: https://orcid.org/0000-0002-2354-8648
repository: https://bioc.r-universe.dev
repository-code: https://github.com/MicrobialGenomics-IrsicaixaOrg/dar
commit: 644510eee97a56f9fd595ba951ec8b5299b27643
url: https://microbialgenomics-irsicaixaorg.github.io/dar/
date-released: '2023-09-21'
contact:
- family-names: Catala-Moll
  given-names: Francesc
  email: fcatala@irsicaixa.es
  orcid: https://orcid.org/0000-0002-2354-8648