Life Sciences Commons^™

Statistical Issues In Proteomic Research, Jeffrey S. Morris

Jeffrey S. Morris

No abstract provided.

Analysis Of Mass Spectrometry Data Using Bayesian Wavelet-Based Functional Mixed Models, Jeffrey S. Morris, Philip J. Brown, Keith A. Baggerly, Kevin R. Coombes

Jeffrey S. Morris

In this chapter, we demonstrate how to analyze MALDI-TOF/SELDITOF mass spectrometry data using the wavelet-based functional mixed model introduced by Morris and Carroll (2006), which generalizes the linear mixed models to the case of functional data. This approach models each spectrum as a function, and is very general, accommodating a broad class of experimental designs and allowing one to model nonparametric functional effects for various factors, which can be conditions of interest (e.g. cancer/normal) or experimental factors (blocking factors). Inference on these functional effects allows us to identify protein peaks related to various outcomes of interest, including dichotomous outcomes, categorical …

Improved Peak Detection And Quantification Of Mass Spectrometry Data Acquired From Surface-Enhanced Laser Desorption And Ionization By Denoising Spectra With The Undecimated Discrete Wavelet Transform, Kevin R. Coombes, Spiros Tsavachidis, Jeffrey S. Morris, Keith A. Baggerly, Henry M. Kuerer

Jeffrey S. Morris

Background: Mass spectrometry, especially surface enhanced laser desorption and ionization (SELDI) is increasingly being used to find disease-related proteomic patterns in complex mixtures of proteins derived from tissue samples or from easily obtained biological fluids such as serum, urine, or nipple aspirate fluid. Questions have been raised about the reproducibility and reliability of peak quantifications using this technology. For example, Yasui and colleagues opted to replace continuous measures of the size of a peak by a simple binary indicator of its presence or absence in their analysis of a set of spectra from prostate cancer patients.

Methods: We collected nipple …