Literature DB >> 19481188

Mixed-model of ANOVA for measurement reproducibility in proteomics.

Catherine Mercier1, Caroline Truntzer, Delphine Pecqueur, Jean-Pascal Gimeno, Guillaume Belz, Pascal Roy.   

Abstract

This work is a statistical analysis of reproducibility of a MALDI-TOF mass spectrometry experiment. Its aim is to evaluate measurement variability and compare peak intensities from two types of MALDI-TOF platforms. We compared and commented on the abilities of Principal Component Analysis and mixed-model analysis of variance to evaluate the biological variability and the technical variability of peak intensities in different patients. The properties and hypotheses of both methods are summarized and applied to spectra from plasma of patients with Hodgkin lymphoma. Principal Component Analysis checks rapidly the balance between the two variabilities; however, a mixed-model analysis of variance is necessary to quantify the biological and technical components of the experimental variance as well as their interactions and to split the total variance into between-subjects and within-subject components. The latter method helped to assess the reproducibility of measurements from two MALDI-TOF platforms and to decompose the technical variability according to the experimental design.

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Year:  2009        PMID: 19481188     DOI: 10.1016/j.jprot.2009.05.005

Source DB:  PubMed          Journal:  J Proteomics        ISSN: 1874-3919            Impact factor:   4.044


  5 in total

Review 1.  Quantitative analysis of glycerophospholipids by LC-MS: acquisition, data handling, and interpretation.

Authors:  David S Myers; Pavlina T Ivanova; Stephen B Milne; H Alex Brown
Journal:  Biochim Biophys Acta       Date:  2011-06-12

2.  Assessing the quality and reproducibility of a proteomic platform for clinical stroke biomarker discovery.

Authors:  Ediri Sideso; Michalis Papadakis; Cynthia Wright; Ashok Handa; Alastair Buchan; Benedikt Kessler; James Kennedy
Journal:  Transl Stroke Res       Date:  2010-08-14       Impact factor: 6.829

3.  Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset.

Authors:  Chris Bauer; Frank Kleinjung; Celia J Smith; Mark W Towers; Ali Tiss; Alexandra Chadt; Tanja Dreja; Dieter Beule; Hadi Al-Hasani; Knut Reinert; Johannes Schuchhardt; Rainer Cramer
Journal:  BMC Bioinformatics       Date:  2011-05-09       Impact factor: 3.169

4.  Variance component analysis of a multi-site study for the reproducibility of multiple reaction monitoring measurements of peptides in human plasma.

Authors:  Jessie Q Xia; Nell Sedransk; Xingdong Feng
Journal:  PLoS One       Date:  2011-01-26       Impact factor: 3.240

5.  PPINGUIN: Peptide Profiling Guided Identification of Proteins improves quantitation of iTRAQ ratios.

Authors:  Chris Bauer; Frank Kleinjung; Dorothea Rutishauser; Christian Panse; Alexandra Chadt; Tanja Dreja; Hadi Al-Hasani; Knut Reinert; Ralph Schlapbach; Johannes Schuchhardt
Journal:  BMC Bioinformatics       Date:  2012-02-16       Impact factor: 3.169

  5 in total

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