Hierarchical Bayesian methods for integration of various types of genomics data

Elizabeth M. Jennings, Jeffrey S. Morris, Raymond J. Carroll, Ganiraju C. Manyam, Veerabhadran Baladandayuthapani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

We propose methods to integrate data across several genomic platforms using a hierarchical Bayesian analysis framework that incorporates the biological relationships among the platforms to identify genes whose expression is related to clinical outcomes in cancer. This integrated approach combines information across all platforms, leading to increased statistical power in finding these predictive genes, and further provides mechanistic information about the manner of the effect on the outcome. We demonstrate the advantages of this approach (including improved estimation via effective estimate shrinkage) through a simulation, and finally we apply our method to a Glioblastoma Multiforme dataset and identify several genes significantly associated with patients' survival.

Original languageEnglish (US)
Title of host publicationProceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012
Pages5-8
Number of pages4
DOIs
StatePublished - 2012
Event2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012 - Washington, DC, United States
Duration: Dec 2 2012Dec 4 2012

Publication series

NameProceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
ISSN (Print)2150-3001
ISSN (Electronic)2150-301X

Other

Other2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012
Country/TerritoryUnited States
CityWashington, DC
Period12/2/1212/4/12

Keywords

  • Bayesian modeling
  • genomics
  • integrative analysis
  • shrinkage priors

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computational Theory and Mathematics
  • Signal Processing
  • Biomedical Engineering

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