MetabolAnalyze (version 1.3.1)

Probabilistic Latent Variable Models for Metabolomic Data

Description

Fits probabilistic principal components analysis, probabilistic principal components and covariates analysis and mixtures of probabilistic principal components models to metabolomic spectral data.

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Version

Install

install.packages('MetabolAnalyze')

Monthly Downloads

313

Version

1.3.1

License

GPL-2

Maintainer

Claire Gormley

Last Published

August 31st, 2019

Functions in MetabolAnalyze (1.3.1)

ppcca.metabol.jack

Fit a probabilistic principal components and covariates analysis model to a metabolomic data set, and assess uncertainty via the jackknife.

ppca.metabol.jack

Fit a probabilistic principal components analysis model to a metabolomic data set, and assess uncertainty via the jackknife.

ppca.metabol

Fit a probabilistic principal components analysis (PPCA) model to a metabolomic data set via the EM algorithm.

mstep1

First M-step of the AECM algorithm when fitting a mixture of PPCA models.

mstep2

Second M-step of the AECM algorithm when fitting a mixture of PPCA models.

UrineSpectra

NMR metabolomic spectra from urine samples of 18 mice.

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.

mppca.scores.plot

Plot scores from a fitted MPPCA model

scaling

Function to scale metabolomic spectral data.

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.

ppcca.scores.plot

Plot scores from a fitted PPCCA model.

standardize

Function to scale covariates.

estep2

Second E step of the AECM algorithm when fitting a mixture of PPCA models.

mppca.loadings.plot

Plot loadings resulting from fitting a MPPCA model.

loadings.plot

Plot loadings.

estep1

First E step of the AECM algorithm when fitting a mixture of PPCA models.

MetabolAnalyze-package

Probabilistic latent variable models for metabolomic data.

Function to plot a heatmap of BIC values.

loadings.jack.plot

Plot loadings and their associated confidence intervals.

Aitken

Assess convergence of an EM algorithm.

BrainSpectra

NMR spectral data from brain tissue samples.