Evaluating Proteomics Imputation Methods with Improved Criteria.

ABSTRACT: Quantitative measurements produced by tandem mass spectrometry proteomics experiments typically contain a large proportion of missing values. Missing values hinder reproducibility, reduce statistical power, and make it difficult to compare across samples or experiments. Although many methods exist for imputing missing values, in practice, the most commonly used methods are among the worst performing. Furthermore, previous benchmarking studies have focused on relatively simple measurements of error such as the mean-squared error between imputed and held-out values. Here we evaluate the performance of commonly used imputation methods using three practical, "downstream-centric" criteria. These criteria measure the ability to identify differentially expressed peptides, generate new quantitativ

SUBMITTER: Harris L 

PROVIDER: S-EPMC10949645 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature