title: A practical approach for determination of mass spectral baselines.
abstract: Precise determination of the baseline levels of mass spectra is critical for identification and quantification of analytes. Herein, we present a practical approach for determination of the baselines of mass spectra acquired under differential conditions. The baseline determined by this approach was the sum of baseline drift and noise level. The baseline drift was determined by averaging a number of lowest ion intensities. The noise level was determined based on the fact that an accelerated intensity change exists from noise to signal. This change was best revealed by the established accumulative layer thickness curve that was derived from the thicknesses of individual deducted layers. Deductions were performed sequentially layer by layer, each of which has a thickness of averaged lowest ion intensities from existing spectral data. The layer where the accelerated intensity change occurred was defined as a transition layer, which was determined from the polynomial regression in the sixth order of the accumulative layer thickness curve followed by resolving the roots of its fourth derivative. We validated the presence of this transition layer through determination of its convergence from various accumulative layer thickness curves generated by varying either the ending or the fineness of the sequential layer deductions. This simple, practical, program-based baseline determination approach should greatly increase the accuracy and consistency of identification and quantification by mass spectrometry, and facilitate the automation of data processing, thereby increasing the power of any high throughput methodology in general and of shotgun lipidomics in particular.
authors.affiliation: Division of Bioorganic Chemistry and Molecular Pharmacology, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
authors.forename: Kui
authors.initials: K
authors.lastname: Yang
authors.forename: Xiaoling
authors.initials: X
authors.lastname: Fang
authors.forename: Richard W
authors.initials: RW
authors.lastname: Gross
authors.forename: Xianlin
authors.initials: X
authors.lastname: Han
mesh_terms: D000465:Algorithms; D000818:Animals; D007477:Ions / Q000737:chemistry; D008055:Lipids / Q000032:analysis / Q000737:chemistry; D013058:Mass Spectrometry / Q000379:methods*; D055432:Metabolomics / Q000379:methods; D051379:Mice; D009206:Myocardium / Q000737:chemistry; D012044:Regression Analysis; D059629:Signal-To-Noise Ratio
chemical_list: D007477:Ions; D008055:Lipids