Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics

HIGHLIGHTS

• who: Marie Chion and collaborators from the Technologie de Troyes, Troyes, FranceEditor: Wout Bittremieux, University of California have published the research work: Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics, in the Journal: (JOURNAL) of March/11,/2022
• what: The authors provide a rigorous multiple imputation strategy leading to a less biased estimation of the parameters` variability thanks to Rubin`s rules. The authors propose a new methodology that starts by imputing missing values at the peptide level and estimating the uncertainty associated with this imputation . . .
  

   

  

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