R: Probabilistic Latent Variable Models for Metabolomic Data

# Probabilistic Latent Variable Models for Metabolomic Data

## Documentation for package ‘MetabolAnalyze’ version 1.3.1

- DESCRIPTION file

## Help Pages

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.