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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 "msqrob2" in publications use:'
type: software
license: Artistic-2.0
title: 'msqrob2: Robust statistical inference for quantitative LC-MS proteomics'
version: 1.13.0
doi: 10.1074/mcp.m115.055897
identifiers:
- type: doi
  value: 10.32614/CRAN.package.msqrob2
abstract: msqrob2 provides a robust linear mixed model framework for assessing differential
  abundance in MS-based Quantitative proteomics experiments. Our workflows can start
  from raw peptide intensities or summarised protein expression values. The model
  parameter estimates can be stabilized by ridge regression, empirical Bayes variance
  estimation and robust M-estimation. msqrob2's hurde workflow can handle missing
  data without having to rely on hard-to-verify imputation assumptions, and, outcompetes
  state-of-the-art methods with and without imputation for both high and low missingness.
  It builds on QFeature infrastructure for quantitative mass spectrometry data to
  store the model results together with the raw data and preprocessed data.
authors:
- family-names: Clement
  given-names: Lieven
  email: lieven.clement@ugent.be
  orcid: https://orcid.org/0000-0002-9050-4370
- family-names: Gatto
  given-names: Laurent
  email: laurent.gatto@uclouvain.be
  orcid: https://orcid.org/0000-0002-1520-2268
- family-names: Crook
  given-names: Oliver M.
  email: oliver.crook@stats.ox.ac.uk
  orcid: https://orcid.org/0000-0001-5669-8506
- family-names: Vandenbulcke
  given-names: Stijn
  email: vandenbulcke.stijn@gmail.com
preferred-citation:
  type: article
  title: Peptide-level Robust Ridge Regression Improves Estimation, Sensitivity, and
    Specificity in Data-dependent Quantitative Label-free Shotgun Proteomics
  authors:
  - family-names: Goeminne
    given-names: Ludger
  - family-names: Gevaert
    given-names: Kris
  - family-names: Clement
    given-names: Lieven
    email: lieven.clement@ugent.be
    orcid: https://orcid.org/0000-0002-9050-4370
  journal: Molecular & Cellular Proteomics
  year: '2016'
  volume: '15'
  issue: '2'
  doi: 10.1074/mcp.m115.055897
  url: https://doi.org/10.1074/mcp.m115.055897
  start: 657-668
repository: https://bioc.r-universe.dev
repository-code: https://github.com/statOmics/msqrob2
commit: f9276cf121b0db642d2b8037ae7791a68cb4b3f6
url: https://github.com/statOmics/msqrob2
contact:
- family-names: Clement
  given-names: Lieven
  email: lieven.clement@ugent.be
  orcid: https://orcid.org/0000-0002-9050-4370
references:
- type: article
  title: Robust Summarization and Inference in Proteome-wide Label-free Quantification
  authors:
  - family-names: Sticker
    given-names: Adriaan
  - family-names: Goeminne
    given-names: Ludger
  - family-names: Martens
    given-names: Lennart
  - family-names: Clement
    given-names: Lieven
  journal: Molecular & Cellular Proteomics
  year: '2020'
  volume: '19'
  issue: '7'
  doi: 10.1074/mcp.ra119.001624
  url: https://doi.org/10.1074/mcp.ra119.001624
  start: 1209-1219
- type: article
  title: 'MSqRob Takes the Missing Hurdle: Uniting Intensity- and Count-Based Proteomics'
  authors:
  - family-names: Sticker
    given-names: Adriaan
  - family-names: Goeminne
    given-names: Ludger
  - family-names: Martens
    given-names: Lennart
  - family-names: Gevaert
    given-names: Kris
  - family-names: Clement
    given-names: Lieven
  journal: Analytical Chemistry
  year: '2020'
  volume: '92'
  issue: '9'
  url: https://doi.org/10.1021/acs.analchem.9b04375
  doi: 10.1021/acs.analchem.9b04375
  start: 6278–6287