greentea

This includes metabolome data of Japanese green tea measured by gas chromatgraphy mass spectrometry. The data matrix contains 30 samples and 225 metabolites.

 datasets

Computing statistical hypothesis testing for loading in principal component analysis (PCA) (Yamamoto, H. et al. (2014) <doi:10.1186/1471-2105-15-51>), orthogonal smoothed PCA (OS-PCA) (Yamamoto, H. et al. (2021) <doi:10.3390/metabo11030149>), one-sided kernel PCA (Yamamoto, H. (2023) <doi:10.51094/jxiv.262>), partial least squares (PLS) and PLS discriminant analysis (PLS-DA) (Yamamoto, H. et al. (2009) <doi:10.1016/j.chemolab.2009.05.006>), PLS with rank order of groups (PLS-ROG) (Yamamoto, H. (2017) <doi:10.1002/cem.2883>), regularized canonical correlation analysis discriminant analysis (RCCA-DA) (Yamamoto, H. et al. (2008) <doi:10.1016/j.bej.2007.12.009>), multiset PLS and PLS-ROG (Yamamoto, H. (2022) <doi:10.1101/2022.08.30.505949>).

Hiroyuki Yamamoto

loadings

Loadings for Principal Component Analysis and Partial Least
Squares

greentea function

The list object "greentea" contains the following elements:
X : Data matrix that include metabolites in each columns.
Y : Dummy matrix that include group information 0,1 in each columns.
D : Differential matrix (Second order).
M : Averaging matrix for repeated data.
y : Ranking of taste in competitive exhibition.

greentea: Metabolome analysis of Japanese green tea

Description

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