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Updated: Feb 11, 2026

Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics
Published on: October 13, 2020
Quantitative quality-assessment techniques to compare fractionation and depletion methods in SELDI-TOF mass
Jaroslaw Harezlak1, Mike Wang, David Christiani
1Department of Biostatistics, Harvard School of Public Health 655 Huntington Avenue Boston, MA 02115, USA. harezlak@post.harvard.edu
Motivation:
Mass spectrometry (MS), such as the surface-enhanced laser desorption and ionization time-of-flight (SELDI-TOF) MS, provides a potentially promising proteomic technology for biomarker discovery. An important matter for such a technology to be used routinely is its reproducibility. It is of significant interest to develop quantitative measures to evaluate the quality and reliability of different experimental methods.
Results:
We compare the quality of SELDI-TOF MS data using unfractionated, fractionated plasma samples and abundant protein depletion methods in terms of the numbers of detected peaks and reliability. Several statistical quality-control and quality-assessment techniques are proposed, including the Graeco-Latin square design for the sample allocation on a Protein chip, the use of the pairwise Pearson correlation coefficient as the similarity measure between the spectra in conjunction with multi-dimensional scaling (MDS) for graphically evaluating similarity of replicates and assessing outlier samples; and the use of the reliability ratio for evaluating reproducibility. Our results show that the number of peaks detected is similar among the three sample preparation technologies, and the use of the Sigma multi-removal kit does not improve peak detection. Fractionation of plasma samples introduces more experimental variability. The peaks detected using the unfractionated plasma samples have the highest reproducibility as determined by the reliability ratio.
Availability:
Our algorithm for assessment of SELDI-TOF experiment quality is available at http://www.biostat.harvard.edu/~xlin.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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