Accessibility navigation

Chromatographic alignment of LC-MS and LC-MS/MS datasets by genetic algorithm feature extraction

Palmblad, M., Mills, D. J., Bindschedler, L.V. and Cramer, R. ORCID: (2007) Chromatographic alignment of LC-MS and LC-MS/MS datasets by genetic algorithm feature extraction. Journal of the American Society for Mass Spectrometry, 18 (10). pp. 1835-1843. ISSN 1044-0305

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1016/j.jasms.2007.07.018


Liquid chromatography-mass spectrometry (LC-MS) datasets can be compared or combined following chromatographic alignment. Here we describe a simple solution to the specific problem of aligning one LC-MS dataset and one LC-MS/MS dataset, acquired on separate instruments from an enzymatic digest of a protein mixture, using feature extraction and a genetic algorithm. First, the LC-MS dataset is searched within a few ppm of the calculated theoretical masses of peptides confidently identified by LC-MS/MS. A piecewise linear function is then fitted to these matched peptides using a genetic algorithm with a fitness function that is insensitive to incorrect matches but sufficiently flexible to adapt to the discrete shifts common when comparing LC datasets. We demonstrate the utility of this method by aligning ion trap LC-MS/MS data with accurate LC-MS data from an FTICR mass spectrometer and show how hybrid datasets can improve peptide and protein identification by combining the speed of the ion trap with the mass accuracy of the FTICR, similar to using a hybrid ion trap-FTICR instrument. We also show that the high resolving power of FTICR can improve precision and linear dynamic range in quantitative proteomics. The alignment software, msalign, is freely available as open source.

Item Type:Article
Divisions:Life Sciences
Life Sciences > School of Biological Sciences > Biomedical Sciences
Life Sciences > School of Chemistry, Food and Pharmacy > Department of Chemistry
Interdisciplinary centres and themes > Chemical Analysis Facility (CAF)
ID Code:11547

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation