Package: rADA 1.1.9

Emma Gail

rADA: Statistical Analysis and Cut-Point Determination of Immunoassays

Systematically transform immunoassay data, evaluate if the data is normally distributed, and pick the right method for cut point determination based on that evaluation. This package can also produce plots that are needed for reports, so data analysis and visualization can be done easily.

Authors:Emma Gail [cre, aut], Lidija Turkovic [aut], Anil Dolgun [ctb], Monther Alhamdoosh [ctb], Milica Ng [ctb]

rADA_1.1.9.tar.gz
rADA_1.1.9.tar.gz(r-4.7-any)rADA_1.1.9.tar.gz(r-4.6-any)
rADA_1.1.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rADA/json (API)

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

On CRAN:

Conda:

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

2.30 score 1 stars 5 scripts 255 downloads 10 exports 110 dependencies

Last updated from:10b8e8e44f. Checks:2 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE141
source / vignettesOK205
linux-release-x86_64NOTE152
wasm-releaseOK133

Exports:assayMeltcalcCvStatscalcScpValuesevalBoxplotevalNormexcludeOutliersimportAssaymixedModelscpscpForestPlot

Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDatacheckmateclasscliclustercolorspacecowplotcpp11data.tableDerivdigestdoBydplyre1071evaluatefarverfastmapfontawesomeforecastforeignforestplotFormulafracdifffsgenericsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclelme4lmerTestlmtestmagrittrMASSMatrixMatrixModelsmatrixStatsmemoisemgcvmicrobenchmarkmimeminqamodelrnlmenloptrnnetnumDerivopenxlsxpbkrtestpillarpkgconfigplyrproxypurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasreshape2rlangrmarkdownrpartrstudioapiS7sassscalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDatetinytexurcautf8vctrsviridisLitewithrxfunyamlzipzoo

Screening Cut Point Determination with rADA
Introduction | Installation | Load Libraries | Read file | Calculate Mean, SD, and CV% | Boxplots of Days/Operators | Evaluating the distribution of the dataset | Normality Evaluation | No Outlier Removal | Outlier Removal | Calculate Cut Point | Forest Plot of Cut Points | References | Session Info
Rendered fromrada_vignette.Rmdusingknitr::knitr

Last update: 2021-03-23
Started: 2021-03-23

Screening Cut Point Determination with rADA
Introduction | Installation | Load Libraries | Read file | Calculate Mean, SD, and CV% | Boxplots of Days/Operators | Evaluating the distribution of the dataset | Normality Evaluation | No Outlier Removal | Outlier Removal | Calculate Cut Point | Forest Plot of Cut Points | Analysis of Variance | The effect of different methodologies on the cut point estimation | References | Session Info
Rendered fromrada_vignette_supplemental.Rmdusingknitr::knitr

Last update: 2021-03-23
Started: 2021-03-23

Readme and manuals

Help Manual

Help pageTopics
Melt Assay DatasetassayMelt
Calculate Coefficient of VariationcalcCvStats calcCvStats,ImmunoAssay-method
Calculate screening cut point values for scp()calcScpValues
Evaluate the Assays with BoxplotsevalBoxplot evalBoxplot,ImmunoAssay-method
Normality EvaluationevalNorm evalNorm,ImmunoAssay-method
Exclude Outliers from Melted Assay DataframeexcludeOutliers
Define ImmunoAssay classImmunoAssay ImmunoAssay-class
Import assay as ImmunoAssay objectimportAssay
Simulated Lognormal DatasetlognormAssay
Mixed model wrapper for assay dataframemixedModel
Calculate screening cut pointscp scp,ImmunoAssay-method
Generate forest plot of SCP valuesscpForestPlot scpForestPlot,ImmunoAssay-method