Differential expression and network inferences through functional data modeling

Donatello Telesca, Lurdes Y.T. Inoue, Mauricio Neira, Ruth Etzioni, Martin Gleave, Colleen Nelson

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Time course microarray data consist of mRNA expression from a common set of genes collected at different time points. Such data are thought to reflect underlying biological processes developing over time. In this article, we propose a model that allows us to examine differential expression and gene network relationships using time course microarray data. We model each gene-expression profile as a random functional transformation of the scale, amplitude, and phase of a common curve. Inferences about the gene-specific amplitude parameters allow us to examine differential gene expression. Inferences about measures of functional similarity based on estimated time-transformation functions allow us to examine gene networks while accounting for features of the gene-expression profiles. We discuss applications to simulated data as well as to microarray data on prostate cancer progression.

Original languageEnglish (US)
Pages (from-to)793-804
Number of pages12
JournalBiometrics
Volume65
Issue number3
DOIs
StatePublished - Sep 1 2009
Externally publishedYes

Fingerprint

Functional Data
Data Modeling
Differential Expression
Data structures
Microarrays
Genes
Gene expression
gene expression
Microarray Data
Gene Expression Profile
Gene Networks
Gene Regulatory Networks
Transcriptome
prostatic neoplasms
Gene
Biological Phenomena
genes
Prostate Cancer
Progression
Messenger RNA

Keywords

  • Bayesian hierarchical model
  • Differential expression
  • Functional data
  • Functional similarity
  • Gene networks
  • Time course microarray data
  • Time transformation

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

Telesca, D., Inoue, L. Y. T., Neira, M., Etzioni, R., Gleave, M., & Nelson, C. (2009). Differential expression and network inferences through functional data modeling. Biometrics, 65(3), 793-804. https://doi.org/10.1111/j.1541-0420.2008.01159.x

Differential expression and network inferences through functional data modeling. / Telesca, Donatello; Inoue, Lurdes Y.T.; Neira, Mauricio; Etzioni, Ruth; Gleave, Martin; Nelson, Colleen.

In: Biometrics, Vol. 65, No. 3, 01.09.2009, p. 793-804.

Research output: Contribution to journalArticle

Telesca, D, Inoue, LYT, Neira, M, Etzioni, R, Gleave, M & Nelson, C 2009, 'Differential expression and network inferences through functional data modeling', Biometrics, vol. 65, no. 3, pp. 793-804. https://doi.org/10.1111/j.1541-0420.2008.01159.x
Telesca D, Inoue LYT, Neira M, Etzioni R, Gleave M, Nelson C. Differential expression and network inferences through functional data modeling. Biometrics. 2009 Sep 1;65(3):793-804. https://doi.org/10.1111/j.1541-0420.2008.01159.x
Telesca, Donatello ; Inoue, Lurdes Y.T. ; Neira, Mauricio ; Etzioni, Ruth ; Gleave, Martin ; Nelson, Colleen. / Differential expression and network inferences through functional data modeling. In: Biometrics. 2009 ; Vol. 65, No. 3. pp. 793-804.
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