Expression ratios correction in TMT (Tandem Mass Tags) labeled peptides
Protein quantitation in MS/MS mode is affected by the problem of peptide expression ratios underestimation. Algorithms to more accurately quantify peptide ratios in MS/MS mode were developed in this thesis. These algorithms attempt to eliminate the existing problem of peptide expression ratios underestimation by computing weighted peptide ratios. Also, a new noise model for TMT labeled data sets is introduced. This noise model is used to compute the statistical reliability of protein expression ratios. We tested the algorithms and the noise model developed on different TMT labeled data sets. The work developed on this thesis, serves as a framework for further improvements of methods for protein quantification in the MS/MS mode using TMT isobaric labeling.