Package: gammaFuncModel 6.0

gammaFuncModel: Non-Linear Mixed Effects Model Based on the Gamma Function Form

Identifies biomarkers that exhibit differential response dynamics by time across groups and estimates kinetic properties of biomarkers.

Authors:Hongting Chen [aut, cre], Liming Liang [aut]

gammaFuncModel_6.0.tar.gz
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manual.pdf |manual.html✨
card.svg |card.png
gammaFuncModel/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.48 score 173 downloads 13 exports 41 dependencies

Last updated from:1529508853. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK117
source / vignettesOK188
linux-release-x86_64OK138
macos-release-arm64OK213
macos-oldrel-arm64OK154
windows-develOK81
windows-releaseOK97
windows-oldrelOK88
wasm-releaseOK103

Exports:calculate_AUCcalculate_Cmaxcalculate_half_lifecalculate_TmaxdiffGrpResponsediffGrpResponse_parallelgammaFunctiongenerate_f_functiongenerate_modelsgeneratePlotgrpResp2TimegrpResp2Time_parallelpk_calculation

Dependencies:clicodetoolscpp11cubaturedigestdplyrfarverfuturefuture.applygenericsggplot2globalsgluegridExtragtableisobandlabelinglatticelifecyclelistenvmagrittrnlmeparallellypatchworkpillarpkgconfigR6rbibutilsRColorBrewerRcppRdpackrlangrootSolveS7scalestibbletidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Function that produces Area Under the Curve(AUC) property for a single individual in a particular group, for a specific metabolitecalculate_AUC
Function that produces Cmax property for a single individual in a particular group, for a specific metabolitecalculate_Cmax
Function that produces Half-life property for a single individual in a particular group, for a specific metabolitecalculate_half_life
Function that produces Tmax property for a single individual in a particular group, for a specific metabolitecalculate_Tmax
Function that produces a summary table for coefficient estimates, their p-values and LRT p-values for every metabolite in the dataframediffGrpResponse
Parallelized version of diffGrpResponse()diffGrpResponse_parallel
Implementation of the novel non-linear mixed-effects model based on gamma function form with nested covariance structure where random effects are specified for each Diet level within each subject (ID), capturing within-subject correlation across dietary conditions. to identify metabolites that responds to time differentially across dietary groupsgammaFunction
Function produce predictions from the modelgenerate_f_function
Function that produces a fitted gamma model for each metabolitegenerate_models
Function that generate plots for metabolite modelsgeneratePlot
Function that produces a summary table for coefficient estimates, their p-values and LRT p-values for every metabolite in the dataframe, for a single GroupgrpResp2Time
Vectorized version of grpRes2Time()grpResp2Time_parallel
Function that returns a data frame for Tmax, Cmax, half-life, AUC and AUCInf for metabolitespk_calculation