In addition to the previous two gold standard datasets, we analyzed dataset PXD020248 where no ratio is known between samples and no spike proteins have been used. Interestingly, in the original manuscript the authors did not use any package for normalization, missing value imputation or downstream analysis. Supplementary Figure shows the CVs for all replicates of PXD020248. For all normalization methods, MSstats shows lower CV values than Proteus; and the values for both tools are quite high compared with the previous analysis PXD007145 (Proteus: 21.16%, MSstats: 16.47% in PXD007145; Proteus: 30.59%, MSstats: 17.52% in PXD020248). With a deeper look into the datasets, PXD007145 and PXD020248 result from quantms we observed a significant variation in the number of missed cleavages and missing values (Figure ). The quantms quality control heatmaps reports of both datasets (Supplementary Figure ) showed this variation at the level of MS run file. This may be the reason why we observed major differences when analyzing the number of DE proteins at different FDR thresholds for different normalization methods (Supplementary Figure ) and little agreement among tools for the final DE proteins (Supplementary Figure ). Intriguingly, Proteus shared less than 20% in all normalization cases with the original author's results while MSstats and the manuscript results shared around ~40% of the reported proteins. While still, MSstats performs relatability better for dataset PXD020248 (like previous results in gold standard datasets), we included these contradictory results to show that data quality may introduce more differences and variability in the results than the tool used to perform the downstream analysis.