Dependent peptide searching is a method for discovering covalently-modified peptides-and therefore proteins-in mass-spectrometry-based proteomics experiments. Being more permissive than standard search methods, it has the potential to discover novel modifications (e.g., post-translational modifications occurring in vivo, or modifications introduced in vitro). However, few studies have explored dependent peptide search results in an untargeted way. In the present study, we sought to evaluate dependent peptide searching as a means of characterising proteins that have been modified in vitro. We generated a model data set by analysing N-ethylmaleimide-treated bovine serum albumin, and performed dependent peptide searches using the popular MaxQuant software. To facilitate interpretation of the search results (hundreds of dependent peptides), we developed a series of visualisation tools (R scripts). We used the tools to assess the diversity of putative modifications in the albumin, and to pinpoint hypothesised modifications. We went on to explore the tools' generality via analyses of public data from studies of rat and human proteomes. Of 19 expected sites of modification (one in rat cofilin-1 and 18 across six different human plasma proteins), eight were found and correctly localised. Apparently, some sites went undetected because chemical enrichment had depleted necessary analytes (potential 'base' peptides). Our results demonstrate (i) the ability of the tools to provide accurate and informative visualisations, and (ii) the usefulness of dependent peptide searching for characterising in vitro protein modifications. Our model data are available via PRIDE/ProteomeXchange (accession number PXD013040).