Literature DB >> 17626063

Quantitative quality-assessment techniques to compare fractionation and depletion methods in SELDI-TOF mass spectrometry experiments.

Jaroslaw Harezlak1, Mike Wang, David Christiani, Xihong Lin.   

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. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 17626063     DOI: 10.1093/bioinformatics/btm346

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  5 in total

1.  Search for breast cancer biomarkers in fractionated serum samples by protein profiling with SELDI-TOF MS.

Authors:  Annemieke W J Opstal-van Winden; Jos H Beijnen; Arnoud Loof; Waander L van Heerde; Roel Vermeulen; Petra H M Peeters; Carla H van Gils
Journal:  J Clin Lab Anal       Date:  2012-01       Impact factor: 2.352

2.  Nonparametric Regression With Missing Outcomes Using Weighted Kernel Estimating Equations.

Authors:  Lu Wang; Andrea Rotnitzky; Xihong Lin
Journal:  J Am Stat Assoc       Date:  2012-01-01       Impact factor: 5.033

3.  Statistical quality assessment and outlier detection for liquid chromatography-mass spectrometry experiments.

Authors:  Ole Schulz-Trieglaff; Egidijus Machtejevas; Knut Reinert; Hartmut Schlüter; Joachim Thiemann; Klaus Unger
Journal:  BioData Min       Date:  2009-04-07       Impact factor: 2.522

4.  Semi-quantitative and structural metabolic phenotyping by direct infusion ion trap mass spectrometry and its application in genetical metabolomics.

Authors:  Albert Koulman; Mingshu Cao; Marty Faville; Geoff Lane; Wade Mace; Susanne Rasmussen
Journal:  Rapid Commun Mass Spectrom       Date:  2009-08       Impact factor: 2.419

5.  Identification of potential prognostic markers for knee osteoarthritis by serum proteomic analysis.

Authors:  Yoshihiko Takinami; Shinya Yoshimatsu; Takaoki Uchiumi; Tomoko Toyosaki-Maeda; Atsushi Morita; Takeshi Ishihara; Shoji Yamane; Isao Fukuda; Hiroyuki Okamoto; Yoshito Numata; Naoshi Fukui
Journal:  Biomark Insights       Date:  2013-07-29
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.