cancerclass-package {cancerclass} | R Documentation

## Development and validation of diagnostic tests from high-dimensional molecular data

### Description

This package implements classification and validation methods for high-dimensional applications, such as gene expression 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 [1]. Methods for calculation and visualization of continuous prediction scores allow to balance sensitivity and specificity and define a cutoff value according to clinical requirements.

### Details

Package: | cancerclass
Type: | Package
Version: | 1.5.1
Date: | 2013-09-04
License: | GPL (>=2)

### Author(s)

Jan Budczies jan.budczies@charite.de, Daniel Kosztyla danielkossi@hotmail.com

### References

[1] Michiels S, Koscielny S, Hill C (2005), Prediction of cancer outcome with microarrays: a multiple random validation strategy, Lancet 365:488-492.

### See Also

`fit`, `GOLUB1`, `loo`, `nvalidate`, `nvalidation-class`, `plot`, `plot,nvalidation-method`, `plot,prediction-method`, `plot,predictor-method`, `plot,validation-method`, `plot3d`, `plot3d,nvalidation-method`, `plot3d,validation-method`, `predict`, `prediction-class`, `predictor-class`, `summary`, `validate`, `validation-class`, `cancerclass-internal`, `ilogit`, `calc.roc`, `calc.auc`, `get.d`, `get.d2`, `get.prop`, `get.ntrain`, `prepare`, `filter`

[Package cancerclass version 1.26.0 Index]