A Time-Series DDP for Functional Proteomics Profiles

Luis E. Nieto-Barajas, Peter Müller, Yuan Ji, Yiling Lu, Gordon Mills

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Using a new type of array technology, the reverse phase protein array (RPPA), we measure time-course protein expression for a set of selected markers that are known to coregulate biological functions in a pathway structure. To accommodate the complex dependent nature of the data, including temporal correlation and pathway dependence for the protein markers, we propose a mixed effects model with temporal and protein-specific components. We develop a sequence of random probability measures (RPM) to account for the dependence in time of the protein expression measurements. Marginally, for each RPM we assume a Dirichlet process model. The dependence is introduced by defining multivariate beta distributions for the unnormalized weights of the stick-breaking representation. We also acknowledge the pathway dependence among proteins via a conditionally autoregressive model. Applying our model to the RPPA data, we reveal a pathway-dependent functional profile for the set of proteins as well as marginal expression profiles over time for individual markers.

Original languageEnglish (US)
Pages (from-to)859-868
Number of pages10
JournalBiometrics
Volume68
Issue number3
DOIs
StatePublished - Sep 1 2012
Externally publishedYes

Fingerprint

Proteomics
proteomics
Time series
time series analysis
Proteins
Protein
Pathway
Protein Array Analysis
proteins
Random Probability Measure
protein synthesis
Reverse
Mixed Effects Model
Dirichlet Process
Beta distribution
Temporal Correlation
Profile
Dependent
Multivariate Distribution
Autoregressive Model

Keywords

  • Bayesian nonparametrics
  • Dependent random measures
  • Markov beta process
  • Mixed effects model
  • Stick-breaking processes
  • Time-series analysis

ASJC Scopus subject areas

  • Statistics and Probability
  • Medicine(all)
  • Immunology and Microbiology(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

Cite this

A Time-Series DDP for Functional Proteomics Profiles. / Nieto-Barajas, Luis E.; Müller, Peter; Ji, Yuan; Lu, Yiling; Mills, Gordon.

In: Biometrics, Vol. 68, No. 3, 01.09.2012, p. 859-868.

Research output: Contribution to journalArticle

Nieto-Barajas, LE, Müller, P, Ji, Y, Lu, Y & Mills, G 2012, 'A Time-Series DDP for Functional Proteomics Profiles', Biometrics, vol. 68, no. 3, pp. 859-868. https://doi.org/10.1111/j.1541-0420.2011.01724.x
Nieto-Barajas, Luis E. ; Müller, Peter ; Ji, Yuan ; Lu, Yiling ; Mills, Gordon. / A Time-Series DDP for Functional Proteomics Profiles. In: Biometrics. 2012 ; Vol. 68, No. 3. pp. 859-868.
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