Package: dtComb 1.0.3

Gokmen Zararsiz

dtComb: Statistical Combination of Diagnostic Tests

A system for combining two diagnostic tests using various approaches that include statistical and machine-learning-based methodologies. These approaches are divided into four groups: linear combination methods, non-linear combination methods, mathematical operators, and machine learning algorithms. See the <https://biotools.erciyes.edu.tr/dtComb/> website for more information, documentation, and examples.

Authors:Serra Ilayda Yerlitas [aut, ctb], Serra Bersan Gengec [aut, ctb], Necla Kochan [aut, ctb], Gozde Erturk Zararsiz [aut, ctb], Selcuk Korkmaz [aut, ctb], Gokmen Zararsiz [aut, ctb, cre]

dtComb_1.0.3.tar.gz
dtComb_1.0.3.zip(r-4.5)dtComb_1.0.3.zip(r-4.4)dtComb_1.0.3.zip(r-4.3)
dtComb_1.0.3.tgz(r-4.4-any)dtComb_1.0.3.tgz(r-4.3-any)
dtComb_1.0.3.tar.gz(r-4.5-noble)dtComb_1.0.3.tar.gz(r-4.4-noble)
dtComb_1.0.3.tgz(r-4.4-emscripten)dtComb_1.0.3.tgz(r-4.3-emscripten)
dtComb.pdf |dtComb.html✨
dtComb/json (API)

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

Peer review:

Bug tracker:https://github.com/gokmenzararsiz/dtcomb/issues

Datasets:
  • allMethods - Includes machine learning models used for the mlComb function
  • exampleData1 - Examples data for the dtComb package
  • exampleData2 - A data set containing the carriers of a rare genetic disorder for 120 samples.
  • exampleData3 - A simulation data containing 250 diseased and 250 healthy individuals.

On CRAN:

13 exports 1.10 score 150 dependencies 7 scripts 211 downloads

Last updated 15 days agofrom:837001bb75. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 02 2024
R-4.5-winOKSep 02 2024
R-4.5-linuxOKSep 02 2024
R-4.4-winOKSep 02 2024
R-4.4-macOKSep 02 2024
R-4.3-winOKSep 02 2024
R-4.3-macOKSep 02 2024

Exports:availableMethodshelper_minimaxhelper_minmaxhelper_PCLhelper_PThelper_TSlinCombmathCombmlCombnonlinCombplotCombstd.traintransform_math

Dependencies:abindaskpassbackportsbase64encBiasedUrnbootbroombslibcachemcarcarDatacaretclassclassIntcliclockcodetoolscolorspacecorrplotcowplotcpp11data.tableDBIDerivdiagramdigestdoBydplyre1071epiRevaluatefansifarverfastmapflextablefontawesomefontBitstreamVerafontLiberationfontquiverforeachfsfuturefuture.applygamgdtoolsgenericsggplot2ggpubrggrepelggsciggsignifglmnetglobalsgluegowergridExtragtablehardhathighrhtmltoolsipredisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvlme4lubridatemagrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminqaModelMetricsmodelrmunsellnlmenloptrnnetnumDerivofficeropensslOptimalCutpointspanderparallellypbkrtestpillarpkgconfigplyrpolynompROCprodlimprogressrproxypurrrquantregR6raggrappdirsRColorBrewerRcppRcppEigenrecipesreshape2rlangrmarkdownrpartrstatixs2sassscalessfshapeSparseMSQUAREMstringistringrsurvivalsyssystemfontstextshapingtibbletidyrtidyselecttimechangetimeDatetinytextzdbunitsutf8uuidvctrsviridisLitewithrwkxfunxml2yamlzipzoo

dtComb

Rendered fromvignettedtComb.Rnwusingknitr::knitron Sep 02 2024.

Last update: 2024-09-01
Started: 2024-08-11

Readme and manuals

Help Manual

Help pageTopics
Includes machine learning models used for the mlComb functionallMethods
Available classification/regression methods in 'dtComb'availableMethods
dtComb: A Comprehensive R Library for Combining Diagnostic TestsdtComb-package dtComb
Examples data for the dtComb packageexampleData1
A data set containing the carriers of a rare genetic disorder for 120 samples.exampleData2
A simulation data containing 250 diseased and 250 healthy individuals.exampleData3
Helper function for minimax method.helper_minimax
Helper function for minmax method.helper_minmax
Helper function for PCL method.helper_PCL
Helper function for PT method.helper_PT
Helper function for TS method.helper_TS
Calculate Cohen's kappa and accuracy.kappa.accuracy
Combine two diagnostic tests with several linear combination methods.linComb
Combine two diagnostic tests with several mathematical operators and distance measures.mathComb
Combine two diagnostic tests with Machine Learning Algorithms.mlComb
Combine two diagnostic tests with several non-linear combination methods.nonlinComb
Plot the combination scores using the training modelplotComb
Predict combination scores and labels for new data sets using the training modelpredict.dtComb
Print the summary of linComb, nonlinComb, mlComb and mathComb functions.print_train
Generate ROC curves and related statistics for the given markers and Combination score.rocsum
Standardization according to the training model parameters.std.test
Standardization according to the chosen method.std.train
Mathematical transformations for biomarkers.transform_math