title: Hierarchical cluster analysis in clinical research with heterogeneous study population: highlighting its visualization with R.
abstract: Big data clinical research typically involves thousands of patients and there are numerous variables available. Conventionally, these variables can be handled by multivariable regression modeling. In this article, the hierarchical cluster analysis (HCA) is introduced. This method is used to explore similarity between observations and/or clusters. The result can be visualized using heat maps and dendrograms. Sometimes, it would be interesting to add scatter plot and smooth lines into the panels of the heat map. The inherent Rheatmappackage does not provide this function. A series of scatter plots can be created usinglatticepackage, and then background color of each panel is mapped to the regression coefficient by using custom-made panel functions. This is the unique feature of thelatticepackage. Dendrograms and color keys can be added as the legend elements of the lattice system. ThelatticeExtrapackage provides some useful functions for the work.
authors.affiliation: Department of Emergency Medicine, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
authors.forename: Zhongheng
authors.initials: Z
authors.lastname: Zhang
authors.affiliation: Big Data Lab, University of Derby, Derby, UK;; Goldsmiths University of London, London, UK.
authors.forename: Fionn
authors.initials: F
authors.lastname: Murtagh
authors.affiliation: Department of Anesthesia, Critical Care, Emergency Medicine and Pain Therapy, Ziekenhuis Oost-Limburg, Genk 3600, Belgium.
authors.forename: Sven
authors.initials: S
authors.lastname: Van Poucke
authors.affiliation: Liver Research Center, First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.
authors.forename: Su
authors.initials: S
authors.lastname: Lin
authors.affiliation: Department of Critical Care Medicine, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Lan
keywords: Hierarchical cluster analysis (HCA); clinical research; dendrogram; heat map