Integrative sparse bayesian analysis of high-dimensional multi-platform genomic data in glioblastoma

Anindya Bhadra, Veerabhadran Baladandayuthapani

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

1 Scopus citations

Abstract

While individual studies have demonstrated that mRNA expressions are affected by both copy number aberrations and microRNAs, their integrative analysis has largely been ignored. In this article, we use high-dimensional regression techniques to perform the integrative analysis of such data in the context of Glioblastoma Multiforme (GBM). It is revealed that copy numbers are more potent regulators of mRNA levels than microRNAs. We also infer the mRNA expression network after adjusting the effect of microRNAs and copy numbers. Our association analysis demonstrates the expression levels of the genes IRS1 and GRB2 are strongly associated with the underlying variations in copy numbers on chromosomal locations 17q25.1 and 3p25.2, but we fail to detect significant associations with microRNA levels.

Original languageEnglish (US)
Title of host publication2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013 - Proceedings
Pages1-4
Number of pages4
DOIs
StatePublished - 2013
Event2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013 - Houston, TX, United States
Duration: Nov 17 2013Nov 19 2013

Publication series

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

Other

Other2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013
Country/TerritoryUnited States
CityHouston, TX
Period11/17/1311/19/13

Keywords

  • Bayesian modeling
  • glioblastoma
  • graphical models
  • high-dimensional data analysis
  • integrative analysis

ASJC Scopus subject areas

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

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