Statistical methods for identifying differentially expressed gene combinations.

Yen Yi Ho, Leslie Cope, Marcel Dettling, Giovanni Parmigiani

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


Identification of coordinate gene expression changes across phenotypes or biological conditions is the basis of the ability to decode the role of gene expression regulatory networks. Statistically, the identification of these changes can be viewed as a search for groups (most typically pairs) of genes whose expression provides better phenotype discrimination when considered jointly than when considered individually. Such groups are defined as being jointly differentially expressed. In this chapter several approaches for identifying jointly differentially expressed groups of genes are reviewed of compared on a set of simulations.

Original languageEnglish (US)
Pages (from-to)171-191
Number of pages21
JournalMethods in molecular biology (Clifton, N.J.)
StatePublished - 2007

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics


Dive into the research topics of 'Statistical methods for identifying differentially expressed gene combinations.'. Together they form a unique fingerprint.

Cite this