Probabilistic Latent Variable Models for Metabolomic Data

Documentation for package ‘MetabolAnalyze’ version 1.3.1

MetabolAnalyze-package	Probabilistic latent variable models for metabolomic data.
BrainSpectra	NMR spectral data from brain tissue samples.
loadings.jack.plot	Plot loadings and their associated confidence intervals.
loadings.plot	Plot loadings.
MetabolAnalyze	Probabilistic latent variable models for metabolomic data.
mppca.loadings.plot	Plot loadings resulting from fitting a MPPCA model.
mppca.metabol	Fit a mixture of probabilistic principal components analysis (MPPCA) model to a metabolomic data set via the EM algorithm to perform simultaneous dimension reduction and clustering.
mppca.scores.plot	Plot scores from a fitted MPPCA model
ppca.metabol	Fit a probabilistic principal components analysis (PPCA) model to a metabolomic data set via the EM algorithm.
ppca.metabol.jack	Fit a probabilistic principal components analysis model to a metabolomic data set, and assess uncertainty via the jackknife.
ppca.scores.plot	Plot scores from a fitted PPCA model
ppcca.metabol	Fit a probabilistic principal components and covariates analysis (PPCCA) model to a metabolomic data set via the EM algorithm.
ppcca.metabol.jack	Fit a probabilistic principal components and covariates analysis model to a metabolomic data set, and assess uncertainty via the jackknife.
ppcca.scores.plot	Plot scores from a fitted PPCCA model.
UrineSpectra	NMR metabolomic spectra from urine samples of 18 mice.