Collection of scripts used to train and validate the classifier presented in
DNA methylation-based classification of central nervous system tumours.
preprocessing.R
Reads raw data, performs normalization, basic filtering and batch effect adjustment.
Normalized and filtered data is stored in ./results
training.R
Trains the Random Forest classifier and stores the final classifier in ./results
cross_validation.R
Performs nested cross-validation and stores the results in ./CV
calibration.R
Evaluates the results of the cross validation and fits the calibration model that is stored in ./results
and
compiles a final report showing classifier performance metrics CVresults.html
.
To train a Random Forest regression model that predicts ABSOLUTE purity of TCGA brain tumor samples, see purity.html
or
purity.Rmd