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-FTICR-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 LC-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.
Yanofsky
Corey M
CM
Bioinformatics Group, Department of Biomedical Engineering, McGill University, Strathcona Building, Montreal, Quebec, Canada. corey.yanofsky@mcgill.ca
Bell
Alexander W
AW
Lesimple
Souad
S
Morales
Frank
F
Lam
Tukiet T
TT
Blakney
Greg T
GT
Marshall
Alan G
AG
Carrillo
Brian
B
Lekpor
Kossi
K
Boismenu
Daniel
D
Kearney
Robert E
RE
D000595:Amino Acid Sequence; D000818:Animals; D002138:Calibration; D002853:Chromatography, Liquid / Q000379:methods*; D013058:Mass Spectrometry / Q000379:methods*; D008969:Molecular Sequence Data; D019151:Peptide Library; D010455:Peptides / Q000032:analysis* / Q000737:chemistry*; D051381:Rats; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*
D019151:Peptide Library; D010455:Peptides