Electron transfer dissociation (ETD) is an alternative peptide dissociation method developed in recent years. Compared with the traditional collision induced dissociation (CID) b and y ion formation, ETD generates c and z ions and the backbone cleavage is believed to be less selective. We have reported previously the application of a statistical data mining strategy, K-means clustering, to discover fragmentation patterns for CID, and here we report application of this approach to ETD spectra. We use ETD data sets from digestions with three different proteases. Data analysis shows that selective cleavages do exist for ETD, with the fragmentation patterns affected by protease, charge states, and amino acid residue compositions. It is also noticed that the c(n-1) ion, corresponding to loss of the C-terminal amino acid residue, is statistically strong regardless of the residue at the C-terminus of the peptide, which suggests that the peptide gas phase conformation plays an important role in the dissociation pathways. These patterns provide a basis for mechanism elucidation, spectral prediction, and improvement of ETD peptide identification algorithms.