학술논문

Quantitative quality-assessment techniques to compare fractionation and depletion methods in SELDI-TOF mass spectrometry experiments.
Document Type
Article
Source
Bioinformatics. Sep2007, Vol. 23 Issue 18, p2441-2441. 1p.
Subject
*MASS spectrometry
*SPECTRUM analysis
*NUCLEAR spectroscopy
*MOUNTAINS
Language
ISSN
1367-4803
Abstract
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 Contact: harezlak@post.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]