Approaches to Sample Size Determination for Multivariate Data: Applications to PCA and PLS-DA of Omics Data.
Sample size determination is a fundamental step in the design of experiments. Methods for sample size determination are abundant for univariate analysis methods, but scarce in the multivariate case. Omics data are multivariate in nature and are commonly investigated using multivariate statistical methods, such as principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). No simple approaches to sample size determination exist for PCA and PLS-DA. In this paper we will introduce important concepts and offer strategies for (minimally) required sample size estimation when planning experiments to be analyzed using PCA and/or PLS-DA.
Laboratory of Systems and Synthetic Biology, Wageningen University and Research Center , Dreijenplein 10, 6703 HB, Wageningen, The Netherlands.
Edoardo
E
Saccenti
Department Psychometrics & Statistics, University of Groningen , Grote Kruissstraat 2/1, 9712 TS, Groningen, The Netherlands.
Marieke E
ME
Timmerman
D000818:Animals; D016002:Discriminant Analysis; D006801:Humans; D016018:Least-Squares Analysis; D055432:Metabolomics / Q000706:statistics & numerical data*; D015999:Multivariate Analysis; D025341:Principal Component Analysis; D018401:Sample Size; D044967:Serum / Q000737:chemistry / Q000378:metabolism; D013552:Swine; D014556:Urine / Q000737:chemistry
covariance estimation; dimensionality; eigenvalue distribution; hypothesis testing; loading estimation; multivariate analysis; power analysis; random matrix theory