Package: cancerclass 1.57.0

Daniel Kosztyla
cancerclass: Development and validation of diagnostic tests from high-dimensional molecular data
The classification protocol starts with a feature selection step and continues with nearest-centroid classification. The accurarcy of the predictor can be evaluated using training and test set validation, leave-one-out cross-validation or in a multiple random validation protocol. Methods for calculation and visualization of continuous prediction scores allow to balance sensitivity and specificity and define a cutoff value according to clinical requirements.
Authors:
cancerclass_1.57.0.tar.gz
cancerclass_1.57.0.zip(r-4.7)cancerclass_1.57.0.zip(r-4.6)cancerclass_1.57.0.zip(r-4.5)
cancerclass_1.57.0.tgz(r-4.6-x86_64)cancerclass_1.57.0.tgz(r-4.6-arm64)cancerclass_1.57.0.tgz(r-4.5-x86_64)cancerclass_1.57.0.tgz(r-4.5-arm64)
cancerclass_1.57.0.tar.gz(r-4.7-arm64)cancerclass_1.57.0.tar.gz(r-4.7-x86_64)cancerclass_1.57.0.tar.gz(r-4.6-arm64)cancerclass_1.57.0.tar.gz(r-4.6-x86_64)
cancerclass_1.57.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
cancerclass/json (API)
| # Install 'cancerclass' in R: |
| install.packages('cancerclass', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:cancerclass-1.57.0(bioc 3.24)cancerclass-1.56.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
cancermicroarrayclassificationvisualization
Last updated from:365b9c6dcf. Checks:1 ERROR, 7 NOTE, 2 OK, 4 WARNING. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 173 | ||
| linux-devel-arm64 | NOTE | 152 | ||
| linux-devel-x86_64 | NOTE | 183 | ||
| source / vignettes | OK | 187 | ||
| linux-release-arm64 | NOTE | 128 | ||
| linux-release-x86_64 | NOTE | 220 | ||
| macos-release-arm64 | WARNING | 84 | ||
| macos-release-x86_64 | WARNING | 325 | ||
| macos-oldrel-arm64 | WARNING | 98 | ||
| macos-oldrel-x86_64 | WARNING | 242 | ||
| windows-devel | NOTE | 105 | ||
| windows-release | NOTE | 114 | ||
| windows-oldrel | NOTE | 94 | ||
| wasm-release | OK | 102 |
Exports:.initFoocalc.auccalc.rocfilterfitget.dget.d2get.lmget.ntrainilogitloonvalidateplotplot3dpredictpreparesummaryvalidate
Dependencies:binomBiobaseBiocGenericsgenerics
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Development and validation of diagnostic tests from high-dimensional molecular data | cancerclass |
| Fitting of a predictor | fit |
| GOLUB DATA | GOLUB GOLUB1 |
| Leave-one-out cross-validation | loo |
| Classification in a multiple random validation protocol in pependence of the number of features used for predictor construction | nvalidate |
| Class "nvalidation" | nvalidation-class |
| Plot Method for 'validation, nvalidation, prediction, predictor' Classes | plot plot,nvalidation-method plot,prediction-method plot,predictor-method plot,validation-method |
| Plot3d method for 'validtion and 'nvalidation' classes | plot3d plot3d,nvalidation-method plot3d,validation-method |
| Predict Method for 'predictor' Class | predict predict,predictor-method predict-methods |
| Class "prediction" | prediction-class |
| Class "predictor" | predictor-class |
| Summary Method for 'prediction' Class | summary summary,prediction-method |
| Classification in a Multiple Random Validation Protocol in Dependence of the Training Set Size | validate |
| Class "validation" | validation-class |