In addition to exploring the performance of these packages to analyze MaxQuant protein results, we are interested to explore the R-packages alternatives to analyze peptide-intensity tables. Most of the tools explored in the present study are designed to perform the downstream analysis based on protein intensity (Perseus, ProVision, LFQ-Analyst, Eatomics). Four tools (MSstats, Proteus, prolfqua, ProStaR) support the data analysis of peptide-level data (Table ). We explored MSstats and Proteus with peptide-intensity results from quantms. Most of the previous benchmark and evaluations has been performed on MaxQuant results which can bias the conclusions. quantms is also a new cloud-based, open-source workflow that enables large-scale proteomics data analysis and generates peptide level quantification and could benefit from this evaluation. We did not evaluate prolfqua and ProStaR because the input to those tools was difficult to be generated from quantms. Firstly, the previous dataset was reanalysed by quantms, and the performance of MSstats and Proteus to analyze quantms peptide results was compared (Figure ). Both tools usually produce fewer false positives than protein-based results-MSstats only got one false positive protein. At the same time, more true positive proteins are detected after filtering with unique peptides for MSstats (29 true positives).