Post-translational modifications (PTMs) of proteins add to the complexity of proteomes, thereby complicating the task of proteome characterization. An efficient strategy to identify this peptide heterogeneity is important for determination of protein function, as well as for mass spectrometry-based protein quantification. Furthermore, studies of allelic variation or single nucleotide polymorphisms (SNPs) at the proteome level, as well as mRNA editing, are increasingly relevant, but validation and determination of false positive rates are challenging. Here we describe an effective workflow for large scale PTM and amino acid substitution identification based on high resolution and high mass accuracy RPLC-MS data sets. A systematic validation strategy of PTMs using RPLC retention time shifts was implemented, and a decision tree for validation is presented. This workflow was applied to Arabidopsis proteome preparations; 1.5 million MS/MS spectra were processed resulting in 20% sequence assignments, with 5% from modified sequences and matching to 2904 proteins; this high assignment rate is in part due to the high quality spectral data. A searchable modified peptide library for Arabidopsis is available online at http://ppdb.tc.cornell.edu/. We discuss confidence in peptide and PTM assignment based on the acquired data set, as well as implications for quantitative analysis of physiologically induced and preparation-related modifications.