title: Power Normalization for Mass Spectrometry Data Analysis and Analytical Method Assessment.
abstract: Biomarker profiling using mass spectrometry plays an essential role in biological studies and is highly dependent on the data analysis for sample classification. In this study, we introduced power nomination of the mass spectra as a method for systematically altering the weights of peaks at different intensity levels. In combination with the use of support vector machine method (SVM), the impact on the sample classification has been characterized using data in four studies previously reported, including the distinctions of anomeric configurations of sugars, types of bacteria, stages of melanoma, and the types of breast cancer. Comprehensive analysis of the data with normalization at different power normalization index (PNI) was developed and analysis tools, including error-PNI plots, reference profiles, and error source profiles, were used to assess the potential of the analytical methods as well as to find the proper approaches to classify the samples.
authors.affiliation: Weldon School of Biomedical Engineering, Purdue University , 206 South Martin Jischke Drive, West Lafayette, Indiana 47907, United States.
authors.forename: Y Melodie
authors.initials: YM
authors.lastname: Du
authors.affiliation: Department of Nanomedicine, Houston Methodist Research Institute , 6565 Fannin Street, Houston, Texas 77030, United States.
authors.forename: Ye
authors.initials: Y
authors.lastname: Hu
authors.affiliation: Department of Chemistry, Purdue University , 560 Oval Drive, West Lafayette, Indiana 47907, United States.
authors.forename: Yu
authors.initials: Y
authors.lastname: Xia
authors.affiliation: Weldon School of Biomedical Engineering, Purdue University , 206 South Martin Jischke Drive, West Lafayette, Indiana 47907, United States.|Department of Chemistry, Purdue University , 560 Oval Drive, West Lafayette, Indiana 47907, United States.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Ouyang
mesh_terms: D013058:Mass Spectrometry / Q000379:methods*; D060388:Support Vector Machine