Circular piecewise regression with applications to cell‐cycle data. Issue 4 (17th March 2016)

• Record Type: Journal Article
• Authors: Rueda, Cristina; Fernández, Miguel A.; Barragán, Sandra; Mardia, Kanti V.; Peddada, Shyamal D.
• Is Part Of: Biometrics. Volume 72:Issue 4(2016)
• Page Start: 1266
• Page End: 1274
• Publication Date: 2016-03-17
• Subjects: Circular data -- Circular–circular regression -- Change points -- Gene expression -- Generalized AIC -- Von Mises distribution; Biometry -- Periodicals; 570.15195
• DOI: 10.1111/biom.12512
• Languages: English
• ISSNs: 0006-341X

Abstract

Summary: Applications of circular regression models appear in many different fields such as evolutionary psychology, motor behavior, biology, and, in particular, in the analysis of gene expressions in oscillatory systems. Specifically, for the gene expression problem, a researcher may be interested in modeling the relationship among the phases of cell‐cycle genes in two species with differing periods. This challenging problem reduces to the problem of constructing a piecewise circular regression model and, with this objective in mind, we propose a flexible circular regression model which allows different parameter values depending on sectors along the circle. We give a detailed interpretation of the parameters in the model and provide maximum likelihood estimators. We also provide a model selection procedure based on the concept of generalized degrees of freedom. The model is then applied to the analysis of two different cell‐cycle data sets and through these examples we highlight the power of our new methodology.