coreferentiality a new method for the hypothesis-based analysis of phenotypes characterized by multivariate datacoreferentiality建立在假说基础上的一种新方法分析表型特征的多元数据.pdfVIP

Coreferentiality: A New Method for the Hypothesis- Based Analysis of Phenotypes Characterized by Multivariate Data Constantin Fesel* ˆ Instituto Gulbenkian de Ciencia, Oeiras, Portugal Abstract Many multifactorial biologic effects, particularly in the context of complex human diseases, are still poorly understood. At the same time, the systematic acquisition of multivariate data has become increasingly easy. The use of such data to analyze and model complex phenotypes, however, remains a challenge. Here, a new analytic approach is described, termed coreferentiality, together with an appropriate statistical test. Coreferentiality is the indirect relation of two variables of functional interest in respect to whether they parallel each other in their respective relatedness to multivariate reference data, which can be informative for a complex effect or phenotype. It is shown that the power of coreferentiality testing is comparable to multiple regression analysis, sufficient even when reference data are informative only to a relatively small extent of 2.5%, and clearly exceeding the power of simple bivariate correlation testing. Thus, coreferentiality testing uses the increased power of multivariate analysis, however, in order to address a more straightforward interpretable bivariate relatedness. Systematic application of this approach could substantially improve the analysis and modeling of complex phenotypes, particularly in the context of human study where addressing functional hypotheses by direct experimentation is often difficult. Citation: Fesel C (2012) Coreferentiality: A New Method for the Hypothesis-Based Analysis of Phenotypes Characterized by Multivariate Data. PLoS ONE 7(3): e33990. doi:10.1371/journal.pone.0033990 Editor: Paul Proost, University of Leuven, Rega Institute, Belgium Re