MS (Master of Science)
Date of Award
Committee Chair or Co-Chairs
Christina Nicole Lewis
JeanMarie Hendrickson, Jeff Knisley
Peptide identification using tandem mass spectrometry depends on matching the observed spectrum with the theoretical spectrum. The raw data from tandem mass spectrometry, however, is often not optimal because it may contain noise or measurement errors. Denoising this data can improve alignment between observed and theoretical spectra and reduce the number of peaks. The method used by Lewis et. al (2018) uses a combined constant and moving threshold to denoise spectra. We compare the effects of using the standard preprocessing methods baseline removal, wavelet smoothing, and binning on spectra with Lewis et. al’s threshold method. We consider individual methods and combinations, using measures of distance from Lewis et. al's scoring function for comparison. Our findings showed that no single method provided better results than Lewis et. al's, but combining techniques with that of Lewis et. al's reduced the distance measurements and size of the data set for many peptides.
Thesis - unrestricted
Carpenter, Skylar, "A Comparison of Standard Denoising Methods for Peptide Identification" (2019). Electronic Theses and Dissertations. Paper 3579. https://dc.etsu.edu/etd/3579
Copyright by the authors.