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Statistical Methods For Holistic Mass Spectral Analysis

Author(s)

John Lu, Charles M. Guttman

Abstract

Analysis of molecular mass distribution data for characterizing the complex synthetic polymer structure has demanded new statistical methods. As with many other high throughput measurement devices, typically only very small number of replicates can be afforded in a given MALDI-TOF mass spectrometry experiment, and hundreds of mass spectral curves for characterizing synthetic polymers are produced on a routine basis. Statistical inference based on experimental data of such mass spectral curves is needed to assess quantitatively the effects due to various instrument-tuning factors or sample heterogeneity in a typical metrological study. This paper provides a broad statistical methodology for holistic analysis of mass spectral curves, including the nonparametric statistical goodness-of-fit tests, entropy and diversity based distributional methods, and relations to earlier approaches proposed in the literature. Several experimental data sets from sample purity study and instrument detector voltage effect are used to illustrate these developed methods.
Citation
J. Amer. Statist. Assoc.

Keywords

Significance tests of curves, goodness of fit tests, analysis of diversity, molecular mass distribution

Citation

Lu, J. and Guttman, C. (1970), Statistical Methods For Holistic Mass Spectral Analysis, J. Amer. Statist. Assoc. (Accessed April 23, 2024)
Created August 26, 2016, Updated January 27, 2020