R is a software environment and programming language for statistical computing and graphics meaning it is applied to process, analyze and plot data. It is free and open source and R packages can be published by every user to provide R functions, compiled code and sample data to others. The following R package are provided by the Seifert group:
This R package provides functions to select relevant variables with mutual impurity reduction (MIR) and to analyze variable relationships with mutual forest impact (MFI). These are further developments of the methods from the SurrogateMinimalDepth package.
Surrogate Minimal Depth
In this R-package functions are provided to select important variables with minimal depth (MD) and surrogate minimal depth (SMD). In addition, variable relations can be investigated by the mean adjusted agreement of surrogate variables. It has been further developed since 2023 under the name RFSurrogates
This R package provides and accompanies the following study. It provides funktions, methods und examples for Double-qpcR experiment (regression) analysis.
Pathway Guided Random Forest
This R package provides functions for the identification of important pathways or variable groups using multiple pathway guided random forest (RF) approaches. Furthermore, it includes functions to simulate pathway based gene expression data under two different scenarios.
This R package provides the experimental benchmark data sets for the Pathway Guided Random Forest approaches.
In this R package various random forest based variable selection approaches like Boruta are reimplemented and provided.