The effects of parsimony logic and extended parsimony clustering on protein identification and quantification in shotgun proteomics

Shotgun proteomics is the most common mass spectrometry-based proteomics method for identifying and quantifying proteins present within a sample. Despite improvements in mass spectrometry tools, the issue dealing with inferring proteins and quantifying them from peptides still persists. The choice of protein sequence databases and the underlying genomic complexities of organisms are often considered sources of peptide degeneracy that lead to varying protein identifications and quantifications. In this thesis, the differences between four protein sequence database sources (Uniprot, NCBI, Ensembl, and IPI) were compared using redundant and non-redundant protein counts and shared and unique peptide counts for two higher eukaryotic organisms (human and mouse) and a representative lower eukaryotic organism (yeast).