A hidden Markov tree model for testing multiple hypotheses corresponding to Gene Ontology gene sets.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Testing predefined gene categories has become a common practice for scientists analyzing high throughput transcriptome data. A systematic way of testing gene categories leads to testing hundreds of null hypotheses that correspond to nodes in a directed acyclic graph. The relationships among gene categories induce logical restrictions among the corresponding null hypotheses. An existing fully Bayesian method is powerful but computationally demanding.

Authors

  • Kun Liang
    Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, N2L 3G1, Canada. kun.liang@uwaterloo.ca.
  • Chuanlong Du
    Department of Statistics, Iowa State University, Ames, 50011, USA.
  • Hankun You
    Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, N2L 3G1, Canada.
  • Dan Nettleton
    Department of Statistics, Iowa State University, Ames, 50011, USA.