title: Integrative correlation: Properties and relation to canonical correlations.
abstract: 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.
authors.affiliation: The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, United States.
authors.forename: Leslie
authors.initials: L
authors.lastname: Cope
authors.affiliation: Department of Applied Math and Statistics, Whiting School of Engineering, The Johns Hopkins University, United States.
authors.forename: Daniel Q
authors.initials: DQ
authors.lastname: Naiman
authors.affiliation: Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, United States ; Department of Biostatistics, Harvard School of Public Health, United States.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Parmigiani
keywords: Bioinformatics; Correlation; Cross-study validation; Gene expression; Reproducibility; Statistics