blockForest: Random Forests for Blocks of Clinical and Omics Covariate Data
Roman Hornung, Marvin N. Wright
A random forest variant suitable for the prediction of binary, survival and continuous outcomes using multi-omics data, i.e., data for which measurements of different types of omics data and/or clinical data for each patient exist. Examples include gene expression measurements, methylation measurements, and copy number variation measurements.
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