Quantitative information on protein abundance is crucial to understand biological processes and is therefore frequently gathered in proteomic studies. However, the quality of a quantitative proteomic dataset is greatly affected by the number of missing values, which need to be minimized to produce robust and meaningful data. In this context, small proteins (≤100 amino acids) pose specific analytical challenges which hinder their efficient identification and quantitative characterization in complex proteomes. In this study, methods for sample preparation and MS-data processing are systematically evaluated for their contribution to identification and quantification of small proteins of C. difficile 630 Δerm.