| Literature DB >> 26028790 |
Leslie Cope1, Daniel Q Naiman2, Giovanni Parmigiani3.
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.Entities:
Keywords: Bioinformatics; Correlation; Cross-study validation; Gene expression; Reproducibility; Statistics
Year: 2014 PMID: 26028790 PMCID: PMC4447241 DOI: 10.1016/j.jmva.2013.09.011
Source DB: PubMed Journal: J Multivar Anal ISSN: 0047-259X Impact factor: 1.473