Systematic evaluation of normalization approaches in tandem mass tag and label-free protein quantification data using PRONE.

ABSTRACT: Despite the significant progress in accuracy and reliability in mass spectrometry technology, as well as the development of strategies based on isotopic labeling or internal standards in recent decades, systematic biases originating from non-biological factors remain a significant challenge in data analysis. In addition, the wide range of available normalization methods renders the choice of a suitable normalization method challenging. We systematically evaluated 17 normalization and 2 batch effect correction methods, originally developed for preprocessing DNA microarray data but widely applied in proteomics, on 6 publicly available spike-in and 3 label-free and tandem mass tag datasets. Opposed to state-of-the-art normalization practice, we found that a reduction in intragroup variation i

SUBMITTER: Arend L 

PROVIDER: S-EPMC12058466 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature