Multicomponent internal recalibration of an LC-FTICR-MS analysis employing a partially characterized complex peptide mixture: Systematic and random errors

In high-throughput proteomics, a promising current approach is the use of liquid chromatography coupled to Fourier transform ion cyclotron resonance mass spectrometry (LC-FFICR-MS) of tryptic peptides from complex mixtures of proteins. To apply this method, it is necessary to account for any systematic measurement error, and it is useful to have an estimate of the random error expected in the measured masses. Here, we analyze by ILC-FTICR-MS a complex mixture of peptides derived from a sample previously characterized by LC-QTOF-MS. Application of a Bayesian probability model of the data and partial knowledge of the composition of the sample suffice to estimate both the systematic and random errors in measured masses.