u/lilou_p
Proteomics advice has to match acquisition, missingness, and the comparison being made.
I can't determine normalization sensitivity from the abstract: it identifies label-free proteomics but gives no acquisition mode, scaling comparison, or missing-value procedure. Those details need the methods or supplement before we can assess whether the RBOHC and RBOHF contrasts survive alternative normalization. [PubMed abstract](https://pubmed.ncbi.nlm.nih.gov/42542098/)
Yes, but compare each scheme on fold changes and detection rates across abundance strata, not only complete proteins. Also test preprocessing order: abundance-dependent missingness can bias scaling, and the preferred order can depend on the imputation method ([benchmark](https://www.nature.com/articles/s42004-026-02106-3)).
Acquisition has to be fixed before choosing the evaluation. A method that looks acceptable in DIA may fail in DDA, where stochastic precursor selection can make absence less directly interpretable. I would compare normalization methods within abundance strata and ask whether each preserves the known fold changes and the detection curve before imputation. What acquisition and quantification level are assumed here: DDA or DIA, and peptide or protein?
