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

    143 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

    ASJC Scopus subject areas

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

    Fingerprint Dive into the research topics of 'Non-parametric quantification of protein lysate arrays'. Together they form a unique fingerprint.

  • Cite this

    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