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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 "ProteoMM" in publications use:'
type: software
license: MIT
title: 'ProteoMM: Multi-Dataset Model-based Differential Expression Proteomics Analysis
  Platform'
version: 1.23.0
doi: 10.32614/CRAN.package.ProteoMM
abstract: ProteoMM is a statistical method to perform model-based peptide-level differential
  expression analysis of single or multiple datasets. For multiple datasets ProteoMM
  produces a single fold change and p-value for each protein across multiple datasets.
  ProteoMM provides functionality for normalization, missing value imputation and
  differential expression. Model-based peptide-level imputation and differential expression
  analysis component of package follows the analysis described in “A statistical framework
  for protein quantitation in bottom-up MS based proteomics" (Karpievitch et al. Bioinformatics
  2009). EigenMS normalisation is implemented as described in "Normalization of peak
  intensities in bottom-up MS-based proteomics using singular value decomposition."
  (Karpievitch et al. Bioinformatics 2009).
authors:
- family-names: Karpievitch
  given-names: Yuliya V
  email: yuliya.k@gmail.com
- family-names: Karpievitch
  given-names: Yuliya V
- family-names: Stuart
  given-names: Tim
- family-names: Mohamed
  given-names: Sufyaan
repository: https://bioc.r-universe.dev
commit: 0473b9a7c7a9fb1fd26447922eaa2829c9bc0817
contact:
- family-names: Karpievitch
  given-names: Yuliya V
  email: yuliya.k@gmail.com