Clustering of liquid chromatography tandem mass-spectrometry data for large scale peptide analysis

Abstract

The clustering of liquid chromatography (LC) tandem mass-spectrometry (MS) data for large scale peptide analysis was discussed. The clustering of ms/ms data of specific peptides detected in separate LC-MS/MS run contribute to peptide identification by improving spectra quality and providing decision-supporting information. The clustering methods were implemented in a software tool, Pep-Miner. The repertoires of MHC Class-I peptides displayed by various cancer cell types in the context of different HLA haplotypes were catalogued and compared by using the Pep-Miner tool. It can also be used to correlate the retention time scale of multiple LC runs and to predict peptide retention times from peptide sequences.