title: Alignment of capillary electrophoresis-mass spectrometry datasets using accurate mass information.
abstract: Capillary electrophoresis-mass spectrometry (CE-MS) is a powerful technique for the analysis of small soluble compounds in biological fluids. A major drawback of CE is the poor migration time reproducibility, which makes it difficult to combine data from different experiments and correctly assign compounds. A number of alignment algorithms have been developed but not all of them can cope with large and irregular time shifts between CE-MS runs. Here we present a genetic algorithm designed for alignment of CE-MS data using accurate mass information. The utility of the algorithm was demonstrated on real data, and the results were compared with one of the existing packages. The new algorithm showed a significant reduction of elution time variation in the aligned datasets. The importance of mass accuracy for the performance of the algorithm was also demonstrated by comparing alignments of datasets from a standard time-of-flight (TOF) instrument with those from the new ultrahigh resolution TOF maXis (Bruker Daltonics).
authors.affiliation: Biomolecular Mass Spectrometry Unit, Department of Parasitology, Leiden University Medical Center, 2300 RC, Leiden, Netherlands. e.nevedomskaya@lumc.nl
authors.forename: Ekaterina
authors.initials: E
authors.lastname: Nevedomskaya
authors.forename: Rico
authors.initials: R
authors.lastname: Derks
authors.forename: André M
authors.initials: AM
authors.lastname: Deelder
authors.forename: Oleg A
authors.initials: OA
authors.lastname: Mayboroda
authors.forename: Magnus
authors.initials: M
authors.lastname: Palmblad
mesh_terms: D000818:Animals; D019075:Electrophoresis, Capillary / Q000379:methods*; D051379:Mice; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*; D013223:Statistics as Topic; D014556:Urine / Q000737:chemistry*