title: Analyzing marginal cases in differential shotgun proteomics.
abstract: CONCLUSIONS
  We present an approach to statistically pinpoint differentially expressed proteins that have quantitation values near the quantitation threshold and are not identified in all replicates (marginal cases). Our method uses a Bayesian strategy to combine parametric statistics with an empirical distribution built from the reproducibility quality of the technical replicates.
  
  
  BACKGROUND
  The software is freely available for academic use at http://pcarvalho.com/patternlab.
authors.affiliation: Center for Technological Development in Health, Oswaldo Cruz Institute, Rio de Janeiro, Brazil. paulo@pcarvalho.com
authors.forename: Paulo C
authors.initials: PC
authors.lastname: Carvalho
authors.forename: Juliana S G
authors.initials: JS
authors.lastname: Fischer
authors.forename: Jonas
authors.initials: J
authors.lastname: Perales
authors.forename: John R
authors.initials: JR
authors.lastname: Yates
authors.forename: Valmir C
authors.initials: VC
authors.lastname: Barbosa
authors.forename: Elias
authors.initials: E
authors.lastname: Bareinboim
mesh_terms: D001499:Bayes Theorem; D011506:Proteins / Q000378:metabolism*; D040901:Proteomics / Q000379:methods*; D012984:Software
chemical_list: D011506:Proteins