Package: iCARH 2.0.2.1
iCARH: Integrative Conditional Autoregressive Horseshoe Model
Implements the integrative conditional autoregressive horseshoe model discussed in Jendoubi, T., Ebbels, T.M. Integrative analysis of time course metabolic data and biomarker discovery. BMC Bioinformatics 21, 11 (2020) <doi:10.1186/s12859-019-3333-0>. The model consists in three levels: Metabolic pathways level modeling interdependencies between variables via a conditional auto-regressive (CAR) component, integrative analysis level to identify potential associations between heterogeneous omic variables via a Horseshoe prior and experimental design level to capture experimental design conditions through a mixed-effects model. The package also provides functions to simulate data from the model, construct pathway matrices, post process and plot model parameters.
Authors:
iCARH_2.0.2.1.tar.gz
iCARH_2.0.2.1.zip(r-4.5)iCARH_2.0.2.1.zip(r-4.4)iCARH_2.0.2.1.zip(r-4.3)
iCARH_2.0.2.1.tgz(r-4.4-any)iCARH_2.0.2.1.tgz(r-4.3-any)
iCARH_2.0.2.1.tar.gz(r-4.5-noble)iCARH_2.0.2.1.tar.gz(r-4.4-noble)
iCARH_2.0.2.1.tgz(r-4.4-emscripten)iCARH_2.0.2.1.tgz(r-4.3-emscripten)
iCARH.pdf |iCARH.html✨
iCARH/json (API)
# Install 'iCARH' in R: |
install.packages('iCARH', repos = c('https://takouajendoubi.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:75dbc3f6d4. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 04 2024 |
R-4.5-win | OK | Nov 04 2024 |
R-4.5-linux | OK | Nov 04 2024 |
R-4.4-win | OK | Nov 04 2024 |
R-4.4-mac | OK | Nov 04 2024 |
R-4.3-win | OK | Nov 04 2024 |
R-4.3-mac | OK | Nov 04 2024 |
Exports:iCARH.checkNormalityiCARH.checkRhatsiCARH.getARCoeffiCARH.getBetaiCARH.getDataImputationiCARH.getPathwaysCoeffiCARH.getPathwaysMatiCARH.getTreatmentEffectiCARH.madiCARH.modeliCARH.paramsiCARH.plotARCoeffiCARH.plotBetaiCARH.plotDataImputationiCARH.plotPathwayPerturbationiCARH.plotTreatmentEffectiCARH.simulateiCARH.waic
Dependencies:abindbackportsBHBiocGenericsbitopsbootbroomcallrcarcarDatacheckmateclicolorspacecorrplotcowplotcpp11DerivdescdistributionaldoBydplyrfansifarverFormulagenericsggplot2ggpubrggrepelggsciggsignifgluegraphgridExtragtableigraphinlineisobandKEGGgraphlabelinglatticelifecyclelme4loomagrittrMASSMatrixMatrixModelsmatrixStatsmc2dmgcvmicrobenchmarkminqamodelrmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgbuildpkgconfigplyrpolynomposteriorprocessxpspurrrquantregQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelRCurlreshape2RgraphvizrlangrstanrstatixscalesSparseMStanHeadersstringistringrsurvivaltensorAtibbletidyrtidyselectutf8vctrsviridisLitewithrXML
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Return model parameters | iCARH.getARCoeff iCARH.getBeta iCARH.getDataImputation iCARH.getPathwaysCoeff iCARH.getTreatmentEffect |
Builds pathways adjacency matrices | iCARH.getPathwaysMat |
Runs the integrative CAR Horseshoe model | iCARH.model |
Summarize and return model parameters | iCARH.params |
Postprocess and plot model parameters | iCARH.checkNormality iCARH.checkRhats iCARH.mad iCARH.plotARCoeff iCARH.plotBeta iCARH.plotDataImputation iCARH.plotPathwayPerturbation iCARH.plotTreatmentEffect iCARH.waic |
Simulates longitudinal data based on the iCARH model. | iCARH.simulate |