Automated Evaluation of Peptide Identifications from Shotgun Proteomics by Use of Reversed-Phase LC Retention Time

摘要

An algorithm based on robust LR has been developed for automated evaluation of peptide matches from database searches by use of peptide retention time in reversed-phase HPLC. The outlier-removal algorithm based on robust LR enables the algorithm to train the LR model on the fly for each search thus the need for internal or external protein or peptide standards is eliminated. A statistical score algorithm was developed for ranking peptide matches based on predicted and observed retention times. This score enables differentiation between true and false matches based on retention time. After removal of peptide matches with insignificant scores based on retention time, higher sensitivities and specificities were achieved and the false positive rates of the searches were significantly lowered as shown by the ROC analysis for all the three database search programs.