Journal
JOURNAL OF PROTEOME RESEARCH
Volume 15, Issue 8, Pages 2379-2393Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.5b01029
Keywords
loading estimation; covariance estimation; eigenvalue distribution; random matrix theory; hypothesis testing; dimensionality; multivariate analysis; power analysis
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Funding
- European Commission [305340]
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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.
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