Package: MetaboDynamics 2.3.0

Katja Danielzik

MetaboDynamics: Bayesian analysis of longitudinal metabolomics data

MetaboDynamics is an R-package that provides a framework of probabilistic models to analyze longitudinal metabolomics data. It enables robust estimation of mean concentrations despite varying spread between timepoints and reports differences between timepoints as well as metabolite specific dynamics profiles that can be used for identifying "dynamics clusters" of metabolites of similar dynamics. Provides probabilistic over-representation analysis of KEGG functional modules and pathways as well as comparison between clusters of different experimental conditions.

Authors:Katja Danielzik [aut, cre], Simo Kitanovski [ctb], Johann Matschke [ctb], Daniel Hoffmann [ctb]

MetaboDynamics_2.3.0.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MetaboDynamics/json (API)

# Install 'MetaboDynamics' in R:
install.packages('MetaboDynamics', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/katjadanielzik/metabodynamics/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • IDs - KEGG ID mapping of metabolites in data set longitudinalMetabolomics
  • longitudinalMetabolomics - A simulated data set of longitudinal concentration tables of metabolites.
  • longitudinalMetabolomics_df - A simulated data set of longitudinal concentration tables of metabolites. In contrast to "longitudinalMetabolomics" this dataset is in data frame format. It was simulated with a different seed compared to longitudinalMetabolomics so the results can deviate.
  • metabolite_modules - KEGG Query Results of experimental metabolites
  • modules_compounds - Background KEGG Query Results Of Functional Modules

On BioConductor:MetaboDynamics-2.3.0(bioc 3.24)MetaboDynamics-2.2.0(bioc 3.23)

softwaremetabolomicsbayesianfunctionalpredictionmultiplecomparisonkeggpathwaystimecourseclusteringdynamicsfunctional-analysislongitudinal-analysismetabolomics-datametabolomics-pipelinecpp

5.85 score 5 stars 3 scripts 318 downloads 15 exports 119 dependencies

Last updated from:4f058a9d16. Checks:1 WARNING, 11 NOTE, 1 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING457
linux-devel-arm64NOTE663
linux-devel-x86_64NOTE743
source / vignettesOK858
linux-release-arm64NOTE647
linux-release-x86_64NOTE730
macos-release-arm64NOTE801
macos-release-x86_64NOTE1378
macos-oldrel-arm64NOTE777
macos-oldrel-x86_64NOTE1144
windows-develNOTE740
windows-releaseNOTE831
windows-oldrelNOTE838
wasm-releaseFAIL224

Exports:cluster_dynamicscompare_dynamicscompare_metabolitesdiagnostics_dynamicsestimates_dynamicsfit_dynamics_modelget_ORA_annotationsheatmap_dynamicsheatmap_metabolitesORA_hypergeometricplot_clusterplot_diagnosticsplot_estimatesplot_ORAplot_PPC

Dependencies:abindapeaplotaskpassbackportsbase64encBHBiobaseBiocGenericsBiostringsbslibcachemcallrcheckmateclicpp11crayoncurlDelayedArraydescdigestdistributionaldplyrdynamicTreeCutevaluatefarverfastmapfontawesomefontBitstreamVerafontLiberationfontquiverfsgdtoolsgenericsGenomicRangesggfunggiraphggplot2ggplotifyggtreegluegridExtragridGraphicsgtablehighrhtmltoolshtmlwidgetshttrinlineIRangesisobandjquerylibjsonliteKEGGRESTknitrlabelinglatticelazyevallifecycleloomagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemimenlmenumDerivopensslotelpatchworkpillarpkgbuildpkgconfigpngposteriorprocessxpspurrrQuickJSRR6rappdirsRColorBrewerRcppRcppEigenRcppParallelrlangrmarkdownrstanrstantoolsS4ArraysS4VectorsS7sassscalesSeqinfoSparseArrayStanHeadersstringistringrSummarizedExperimentsyssystemfontstensorAtibbletidyrtidyselecttidytreetinytextreeioutf8vctrsviridisLitewithrxfunXVectoryamlyulab.utils

MetaboDynamics: analyzing longitudinal metabolomics data with probabilistic models
Data requirements | Analysis time | Background | Setup: load required packages | Load data and plot data overview | Model dynamics | sd per time point | sd per condition | Model outputs | Differences of metabolite abundances between time points | Difference of dynamics between experimental conditions | Dynamic profiles | Cluster dynamics | Over-representation analysis of functional modules in dynamics clusters | Comparison of clusters of different experimental conditions | Dynamics | Metabolites | Combine both
Rendered fromMetaboDynamics.Rmdusingknitr::rmarkdown

Last update: 2026-04-25
Started: 2024-12-20

Using MetaboDynamics with data frames
Background | Setup: load required packages | Load data | Model dynamics | Extract estimates and visualize results | Clustering dynamics | Over-Representation Analysis (ORA) | Compare dynamics clusters | Dynamics | Metabolites | Combine both
Rendered fromMetaboDynamics_dataframes.Rmdusingknitr::rmarkdown

Last update: 2026-03-26
Started: 2025-07-23

Readme and manuals

Help Manual

Help pageTopics
cluster dynamics profiles of metabolitescluster_dynamics
Comparison of metabolite dynamics clusters under different experimental conditionscompare_dynamics
Comparison of metabolite sets between dynamics clusters of different experimental conditionscompare_metabolites
Extracts diagnostic criteria from numeric fit of Bayesian model of dynamicsdiagnostics_dynamics
Extracts parameter estimates from numeric fit of Bayesian model of dynamicsestimates_dynamics
Fits dynamics modelfit_dynamics_model
Retrieve background and annotation information for over-representation analysis (ORA)get_ORA_annotations
plot bubble heatmap from the numerical fit of compare_dynamics()heatmap_dynamics
plot heatmap from comparison of metabolite composition compare_metabolites()heatmap_metabolites
KEGG ID mapping of metabolites in data set longitudinalMetabolomicsIDs
A simulated data set of longitudinal concentration tables of metabolites.longitudinalMetabolomics
A simulated data set of longitudinal concentration tables of metabolites. In contrast to "longitudinalMetabolomics" this dataset is in data frame format. It was simulated with a different seed compared to longitudinalMetabolomics so the results can deviate.longitudinalMetabolomics_df
KEGG Query Results of experimental metabolitesmetabolite_modules
Background KEGG Query Results Of Functional Modulesmodules_compounds
OverRepresentationAnalysis with a hypergeometric modelORA_hypergeometric
visualize clustering solution of cluster_dynamics()plot_cluster
Plot diagnostic criteria of numerical fit of Bayesian model of dynamicsplot_diagnostics
Visualization of parameter estimates from numeric fit of Bayesian model of dynamicsplot_estimates
Plot results of over-representation analysis with ORA_hypergeometric()plot_ORA
Plots posterior predictive check of numerical fit of Bayesian dynamics modelplot_PPC