Non-parametric quantification of protein lysate arrays

Jianhua Hu, Xuming He, Keith A. Baggerly, Kevin R. Coombes, Bryan T.J. Hennessy, Gordon B. Mills

Research output: Contribution to journalArticle

144 Scopus citations

Abstract

Motivation: Proteins play a crucial role in biological activity, so much can be learned from measuring protein expression and post-translational modification quantitatively. The reverse-phase protein lysate arrays allow us to quantify the relative expression levels of a protein in many different cellular samples simultaneously. Existing approaches to quantify protein arrays use parametric response curves fit to dilution series data. The results can be biased when the parametric function does not fit the data. Results: We propose a non-parametric approach which adapts to any monotone response curve. The non-parametric approach is shown to be promising via both simulation and real data studies; it reduces the bias due to model misspecification and protects against outliers in the data. The non-parametric approach enables more reliable quantification of protein lysate arrays.

Original languageEnglish (US)
Pages (from-to)1986-1994
Number of pages9
JournalBioinformatics
Volume23
Issue number15
DOIs
StatePublished - Aug 1 2007
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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    Hu, J., He, X., Baggerly, K. A., Coombes, K. R., Hennessy, B. T. J., & Mills, G. B. (2007). Non-parametric quantification of protein lysate arrays. Bioinformatics, 23(15), 1986-1994. https://doi.org/10.1093/bioinformatics/btm283