Integrative correlation: Properties and relation to canonical correlations

Leslie Cope, Daniel Q. Naiman, Giovanni Parmigiani

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


The integrative correlation coefficient was developed to facilitate the validation of expression microarray results in public datasets, by identifying genes that are reproducibly measured across studies and even across microarray platforms. In the current study, we develop a number of interesting and important mathematical and statistical properties of the integrative correlation coefficient, including a unique permutation-based null distribution with the unusual property that the variance does not shrink as the sample size increases, discussing how these findings impact its use and interpretation, and what they have to say about any method for identifying reproducible genes in a meta-analysis.

Original languageEnglish (US)
Pages (from-to)270-280
Number of pages11
JournalJournal of Multivariate Analysis
StatePublished - Jan 2014


  • 62H20
  • 62P10
  • Bioinformatics
  • Correlation
  • Cross-study validation
  • Gene expression
  • Reproducibility
  • Statistics

ASJC Scopus subject areas

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty


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