Disclosed are methods for recalibrating mass spectrometry data that provide improvement in both mass accuracy and precision by adjusting for experimental variance in parameters that have a substantial impact on mass measurement accuracy. Optimal coefficients are determined using correlated pairs of mass values compiled by matching sets of measured and putative mass values that minimize overall effective mass error and mass error spread. Coefficients are subsequently used to correct mass values for peaks detected in the measured dataset, providing recalibration thereof. Sub-ppm mass measurement accuracy has been demonstrated on a complex fungal proteome after recalibration, providing improved confidence for peptide identifications.
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
The invention was made with Government support under Contract DE-AC05-76RL01830 awarded by the U.S. Department of Energy. The Government has certain rights in the invention.