We present ProtCV (Protein Clustering and Visualization) a new software tool for grouping samples (mass spectra peak-lists) emanating from a high throughput proteomics analysis based on their spectral similarities, and summarizing effectively for the user the clustering results using advanced visualization methods. A unique feature of ProtCV is that it can compare clustering methods applied to the same data set based on several validity in dices to assist the user identify groupings that seem to capture best the underlying structure of the data set. Moreover, ProtCV can assist in formulating hypotheses about the potential role of unidentified proteins in a cluster, identify sets of proteins which act jointly at a specific biological state etc. All these data set mining and exploration operations are very useful for interpreting the results of high throughput MS based proteomics analyses that are commonly used for biomarkers discovery.