title: Proportionality: a valid alternative to correlation for relative data.
abstract: In the life sciences, many measurement methods yield only the relative abundances of different components in a sample. With such relative-or compositional-data, differential expression needs careful interpretation, and correlation-a statistical workhorse for analyzing pairwise relationships-is an inappropriate measure of association. Using yeast gene expression data we show how correlation can be misleading and present proportionality as a valid alternative for relative data. We show how the strength of proportionality between two variables can be meaningfully and interpretably described by a new statistic ϕ which can be used instead of correlation as the basis of familiar analyses and visualisation methods, including co-expression networks and clustered heatmaps. While the main aim of this study is to present proportionality as a means to analyse relative data, it also raises intriguing questions about the molecular mechanisms underlying the proportional regulation of a range of yeast genes.
authors.affiliation: Queensland University of Technology, Brisbane, Australia.
authors.forename: David
authors.initials: D
authors.lastname: Lovell
authors.affiliation: Dept. d'Informàtica, Matemàtica Aplicada i Estadística. U. de Girona, España.
authors.forename: Vera
authors.initials: V
authors.lastname: Pawlowsky-Glahn
authors.affiliation: Dept. Applied Mathematics III, U. Politécnica de Catalunya, Barcelona, Spain.
authors.forename: Juan José
authors.initials: JJ
authors.lastname: Egozcue
authors.affiliation: MRC Clinical Sciences Centre, Imperial College London, United Kingdom.
authors.forename: Samuel
authors.initials: S
authors.lastname: Marguerat
authors.affiliation: Research Department of Genetics, Evolution and Environment, University College London, United Kingdom.
authors.forename: Jürg
authors.initials: J
authors.lastname: Bähler
mesh_terms: D019295:Computational Biology / Q000379:methods*; D015966:Gene Expression Regulation, Fungal / Q000235:genetics; D008957:Models, Genetic; D015233:Models, Statistical; D012331:RNA, Fungal / Q000235:genetics; D012333:RNA, Messenger / Q000235:genetics; D012107:Research Design; D015003:Yeasts / Q000235:genetics
chemical_list: D012331:RNA, Fungal; D012333:RNA, Messenger