Package: multimedia 0.2.1

multimedia: Multimodal Mediation Analysis

Multimodal mediation analysis is an emerging problem in microbiome data analysis. Multimedia make advanced mediation analysis techniques easy to use, ensuring that all statistical components are transparent and adaptable to specific problem contexts. The package provides a uniform interface to direct and indirect effect estimation, synthetic null hypothesis testing, bootstrap confidence interval construction, and sensitivity analysis. More details are available in Jiang et al. (2024) "multimedia: Multimodal Mediation Analysis of Microbiome Data" <doi:10.1101/2024.03.27.587024>.

Authors:Kris Sankaran [aut, cre], Hanying Jiang [aut]

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multimedia.pdf |multimedia.html✨
multimedia/json (API)
NEWS

# Install 'multimedia' in R:
install.packages('multimedia', repos = c('https://krisrs1128.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/krisrs1128/multimedia/issues

Pkgdown site:https://krisrs1128.github.io

Datasets:

On CRAN:

Conda:

coveragemicrobiomeregressionsequencingsoftwarestatisticalmethodstructuralequationmodelscausal-inferencedata-integrationmediation-analysis

5.56 score 1 stars 13 scripts 157 downloads 55 exports 131 dependencies

Last updated 25 days agofrom:b8ce926bca. Checks:1 OK, 7 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 15 2025
R-4.5-winNOTEFeb 15 2025
R-4.5-macNOTEFeb 15 2025
R-4.5-linuxNOTEFeb 15 2025
R-4.4-winNOTEFeb 15 2025
R-4.4-macNOTEFeb 15 2025
R-4.3-winNOTEFeb 15 2025
R-4.3-macNOTEFeb 15 2025

Exports:ansi_aware_handlerbind_mediationbootstrapbrms_modelbrms_samplercontrast_predictionscontrast_samplesdemo_joydemo_splinedirect_effectedgeseffect_summaryestimateestimatorexper_dffdr_summaryglmnet_modelglmnet_samplerindirect_overallindirect_pathwiselm_modellm_samplerlnm_modellnm_samplermediation_datamediation_modelsmediatorsmediators<-multimedian_mediatorsn_outcomesnrownull_contrastnullifyoutcome_modeloutcome_modelsoutcomesoutcomes<-parallelizeplot_mediatorsplot_sensitivitypredictpredict_acrosspretreatmentspretreatments<-retrieve_namesrf_modelrf_samplersamplesensitivitysensitivity_pathwisesensitivity_perturbsetup_profiletreatmentstreatments<-

Dependencies:abindade4apeaskpassbackportsbayesplotBHBiobaseBiocGenericsbiomformatBiostringsbridgesamplingbrmsBrobdingnagcallrcheckmatecliclustercodacodetoolscolorspacecpp11crayoncurldata.tableDelayedArraydescdigestdistributionaldplyrfansifarverforeachformula.toolsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggridgesglmnetglmnetUtilsglobalsgluegridExtragtablehmshttrigraphinlineIRangesisobanditeratorsjsonlitelabelinglatticelifecyclelistenvloomagrittrMASSMatrixMatrixGenericsmatrixStatsmgcvmimeminiLNMmulttestmunsellmvtnormnleqslvnlmenumDerivopenssloperator.toolsparallellypatchworkpermutephyloseqpillarpixmappkgbuildpkgconfigplyrposteriorprettyunitsprocessxprogresspspurrrQuickJSRR6rangerRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelreshape2rhdf5rhdf5filtersRhdf5librlangrstanrstantoolsS4ArraysS4VectorsscalesshapespSparseArrayStanHeadersstringistringrSummarizedExperimentsurvivalsystensorAtibbletidygraphtidyrtidyselectUCSC.utilsutf8vctrsveganviridisLitewithrXVector

Illustration with Nonlinear Effects

Rendered fromillustration.Rmdusingknitr::rmarkdownon Feb 15 2025.

Last update: 2024-09-16
Started: 2024-01-09

Microbiome - Metabolome Mediation Analysis

Rendered fromIBD.Rmdusingknitr::rmarkdownon Feb 15 2025.

Last update: 2024-09-16
Started: 2023-12-18

Quick Start with Random Data

Rendered fromrandom.Rmdusingknitr::rmarkdownon Feb 15 2025.

Last update: 2024-09-16
Started: 2024-03-14

The Mindfulness Study

Rendered frommindfulness.Rmdusingknitr::rmarkdownon Feb 15 2025.

Last update: 2024-09-17
Started: 2023-12-19

Readme and manuals

Help Manual

Help pageTopics
Subset a mediation dataset[,mediation_data,ANY,ANY,ANY-method
Pretty Printingansi_aware_handler
Convert 'mediation_data' to a single data.framebind_mediation
Bootstrap Distribution for Estimatorsbootstrap
Bayesian Regression Model across Responsesbrms_model
Sample from a Bayesian Regression Modelbrms_sampler
Estimate the Difference between Profilescontrast_predictions
Difference between Samples at Contrasting Profilescontrast_samples
A Demo Dataset (Random)demo_joy
A Demo Dataset (Spline)demo_spline
Direct Effects from Estimated Modeldirect_effect
Graphical Structure for Mediation Objectsedges
Access Mediation Model DAGedges,multimedia-method
Average Effects across jeffect_summary
Estimate a Mediation Modelestimate
Accessor for Model Estimatorsestimator
Accessor for Estimatorsestimator,model-method
Convert a Summarized Experiment to a data.frameexper_df
Calibration using Synthetic Nullsfdr_summary
Regularized 'Glmnet' Model across Responsesglmnet_model
Sample from a 'Glmnet' Package Modelglmnet_sampler
Overall Indirect Effectindirect_overall
Indirect Effects via Single Mediation Pathsindirect_pathwise
Linear Model across Responseslm_model
Sample a Linear Modellm_sampler
Logistic Normal Multinomial Modellnm_model
Sample from the Logistic Normal Multinomiallnm_sampler
'mediation_data' Constructormediation_data
Accessor for Outcome Modelsmediation_models
Access Class-Specific Mediatorsmediators
Access to @mediators in Mediation Datamediators,mediation_data-method
Names of Mediators in a Multimedia Objectmediators,multimedia-method
Set Mediatorsmediators<-
Set the Mediators in a Mediation Data Objectmediators<-,mediation_data-method
Mindfulness Datasetmindfulness
Representation of an Outcome or Mediation Modelmodel-class
'multimedia' Constructormultimedia
Number of Mediators in a Multimedia Objectn_mediators
Number of Outcomes in a Multimedia Objectn_outcomes
How many samples in the mediation dataset?nrow,mediation_data-method
Compare Effects from Experimental vs. Null Mediation Datanull_contrast
Nullify Active Edgesnullify
Access the Outcome Model in a Multimedia Objectoutcome_model
Accessor for Outcome Modelsoutcome_models
Access Outcomesoutcomes
Outcomes Data in a Mediation Data Objectoutcomes,mediation_data-method
Names of Outcomes in a Multimedia Objectoutcomes,multimedia-method
Set Outcomes This is an setter method for outcomes in an S4 object, usually of class mediation_data.outcomes<-
Set the Outcomes in a Mediation Data Objectoutcomes<-,mediation_data-method
Parallelize Estimation across Responsesparallelize
Visualize Indirect Effectsplot_mediators
Generic Sensitivity Plotplot_sensitivity
Predict a Subset of Responsespredict_across
Predictions from a Multimedia Classpredict,multimedia-method
Access Pretreatmentspretreatments
Pretreatments in a Mediation Data Objectpretreatments,mediation_data-method
Set Pretreatments This is an setter method for pretreatments in an S4 object, usually of class mediation_data.pretreatments<-
Set the Pretreatments in a Mediation Data Objectpretreatments<-,mediation_data-method
Variables in a Multimedia Objectretrieve_names
Random Forest Modelrf_model
Sample from a Random Forest Modelrf_sampler
Sample New Mediator/Outcome Datasample,multimedia-method
Sensitivity Analysis for Overall Indirect Effectsensitivity
Sensitivity Analysis for Pathwise Indirect Effectssensitivity_pathwise
Sensitivity to User-Specified Perturbationssensitivity_perturb
Define a 'treatment_profile' objectsetup_profile
Generate Random Splinespline_fun
Helper to Modify Formulassub_formula
Define a Treatment Profiletreatment_profile-class
Access Treatmentstreatments
Treatments in a Mediation Data Objecttreatments,mediation_data-method
Names of Treatments in a Multimedia Objecttreatments,multimedia-method
Set Treatments This is an setter method for treatments in an S4 object, usually of class mediation_data.treatments<-
Set the Treatments in a Mediation Data Objecttreatments<-,mediation_data-method