title: Calibration of multivariate scatter plots for exploratory analysis of relations within and between sets of variables in genomic research.
abstract: The scatter plot is a well known and easily applicable graphical tool to explore relationships between two quantitative variables. For the exploration of relations between multiple variables, generalisations of the scatter plot are useful. We present an overview of multivariate scatter plots focussing on the following situations. Firstly, we look at a scatter plot for portraying relations between quantitative variables within one data matrix. Secondly, we discuss a similar plot for the case of qualitative variables. Thirdly, we describe scatter plots for the relationships between two sets of variables where we focus on correlations. Finally, we treat plots of the relationships between multiple response and predictor variables, focussing on the matrix of regression coefficients. We will present both known and new results, where an important original contribution concerns a procedure for the inclusion of scales for the variables in multivariate scatter plots. We provide software for drawing such scales. We illustrate the construction and interpretation of the plots by means of examples on data collected in a genomic research program on taste in tomato.
authors.affiliation: Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, Avinguda Diagonal 647, 08028 Barcelona, Spain. jan.graffelman@upc.edu
authors.forename: Jan
authors.initials: J
authors.lastname: Graffelman
authors.forename: Fred
authors.initials: F
authors.lastname: van Eeuwijk
mesh_terms: D000465:Algorithms; D005819:Genetic Markers; D023281:Genomics / Q000592:standards / Q000706:statistics & numerical data*; D005838:Genotype; D018551:Solanum lycopersicum / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D015999:Multivariate Analysis; D010641:Phenotype; D025341:Principal Component Analysis; D012044:Regression Analysis; D012984:Software
chemical_list: D005819:Genetic Markers