Performs the Principal Component Partial Rsquared method (PCPR2) on omics data and corresponding metadata. PCPR2 is a statistical method, developed by Fages et al. (2014), that investigates sources of variability in metabolomics or other omics data. In brief, it combines features of principal component analysis and multivariable linear regression. The input is X, a complete matrix of omics data and Z, a corresponding data frame of subject metadata. The output is a set of Rpartial2 values, or the proportion of variation in the omics data attributed to each Zvariable.
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Maintainer  
License  MIT 
Version  0.0.0.9000 
Package repository  View on GitHub 
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