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Quantitative Performance Evaluator for Proteomics (QPEP): Web-based Application for Reproducible Evaluation of Proteomics Preprocessing Methods.
Strbenac, Dario; Zhong, Ling; Raftery, Mark J; Wang, Penghao; Wilson, Susan R; Armstrong, Nicola J; Yang, Jean Y H.
Afiliação
  • Strbenac D; School of Mathematics and Statistics, University of Sydney , Sydney, New South Wales 2006, Australia.
  • Zhong L; Bioanalytical Mass Spectrometry Facility, University of New South Wales , Sydney, New South Wales 2052, Australia.
  • Raftery MJ; Bioanalytical Mass Spectrometry Facility, University of New South Wales , Sydney, New South Wales 2052, Australia.
  • Wang P; School of Mathematics and Statistics, University of Sydney , Sydney, New South Wales 2006, Australia.
  • Wilson SR; School of Mathematics & Statistics, University of New South Wales , Sydney, New South Wales 2052, Australia.
  • Armstrong NJ; Centre for Mathematics and its Applications, Mathematical Sciences Institute, Australian National University , Canberra, Australian Capital Territory 0200, Australia.
  • Yang JYH; School of Mathematics and Statistics, University of Sydney , Sydney, New South Wales 2006, Australia.
J Proteome Res ; 16(7): 2359-2369, 2017 07 07.
Article em En | MEDLINE | ID: mdl-28580786
ABSTRACT
Tandem mass spectrometry is one of the most popular techniques for quantitation of proteomes. There exists a large variety of options in each stage of data preprocessing that impact the bias and variance of the summarized protein-level values. Using a newly released data set satisfying a replicated Latin squares design, a diverse set of performance metrics has been developed and implemented in a web-based application, Quantitative Performance Evaluator for Proteomics (QPEP). QPEP has the flexibility to allow users to apply their own method to preprocess this data set and share the results, allowing direct and straightforward comparison of new methodologies. Application of these new metrics to three case studies highlights that (i) the summarization of peptides to proteins is robust to the choice of peptide summary used, (ii) the differences between iTRAQ labels are stronger than the differences between experimental runs, and (iii) the commercial software ProteinPilot performs equivalently well at between-sample normalization to more complicated methods developed by academics. Importantly, finding (ii) underscores the benefits of using the principles of randomization and blocking to avoid the experimental measurements being confounded by technical factors. Data are available via ProteomeXchange with identifier PXD003608.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Peptídeos / Software / Proteoma / Proteínas de Saccharomyces cerevisiae / Proteômica / Espectrometria de Massas em Tandem Tipo de estudo: Clinical_trials / Prognostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Peptídeos / Software / Proteoma / Proteínas de Saccharomyces cerevisiae / Proteômica / Espectrometria de Massas em Tandem Tipo de estudo: Clinical_trials / Prognostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article