Liggett Jr, W.
, Barker, P.
, Semmes, O.
and Cazares, L.
(2021),
Data-Driven and Peak-Based Feature Selection In Serum Protein Mass Spectrometry, Clinical Chemistry
(Accessed January 25, 2025)
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Data-Driven and Peak-Based Feature Selection In Serum Protein Mass Spectrometry
Published
Author(s)
, , O J. Semmes, L H. Cazares
Abstract
Consider functional canonical correlation analysis (CCA) applied to disjoint sections of lengthy protein mass spectra for the purpose of finding long-distance correlation structure. The relations between the CCA weight functions, which are derived from the data, and spectral peaks, which can be traced to individual proteins, provide a basis for interpreting the structure. The data analyzed consist of repeated measurements of a human serum standard by surface-enhanced laser desorption/ionization (SELDI) time-of-flight (TOF) mass spectrometry. There are 88 spectra obtained from 11 protein chips each with 8 spots. The data-analysis goal is insight into the sample preparation step in such spectrometry, a step that involves the protein chip. We see that variation in this step has an outsized effect on a few proteins. We obtain this insight through interpretation of the long-distance correlation structure and through comparison of spectral variation from chip to chip with variation from spot to spot on single chips.Citation
Clinical Chemistry
Pub Type
Journals
Keywords
biomarker validation, SELDI-TOF, serum proteomics
Citation
Issues
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Created October 12, 2021