Bottom-up proteomics provides peptide measurements and has beeninvaluable for moving proteomics into large-scale analyses. Commonly, a singlequantitative value is reported for each protein-coding gene by aggregating peptidequantities into protein groups following protein inference or parsimony. However, giventhe complexity of both RNA splicing and post-translational protein modification, it isoverly simplistic to assume that all peptides that map to a singular protein-coding genewill demonstrate the same quantitative response. By assuming that all peptides from aprotein-coding sequence are representative of the same protein, we may miss thediscovery of important biological differences. To capture the contributions of existingproteoforms, we need to reconsider the practice of aggregating protein values to a singlequantity per protein-coding gene.