R packages

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:

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.

Github: https://github.com/StephanSeifert/SurrogateMinimalDepth
Publikation: Stephan Seifert, Sven Gundlach, Silke Szymczak Bioinformatics 35, 3663-3671 (2019)

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.

Github: https://github.com/szymczak-lab/PathwayGuidedRF
Publikation: Stephan Seifert, Sven Gundlach, Olaf Junge, Silke Szymczak Bioinformatics 36, 4301-4308 (2020)

DataPathwayGuidedRF

This R package provides the experimental benchmark data sets for the Pathway Guided Random Forest approaches.

Github: https://github.com/szymczak-lab/DataPathwayGuidedRF
Publikation: Stephan Seifert, Sven Gundlach, Olaf Junge, Silke Szymczak Bioinformatics 36, 4301-4308 (2020)

Pomona

In this R package various random forest based variable selection approaches like Boruta are reimplemented and provided.

Github: https://github.com/silkeszy/Pomona
Publikation: Frauke Degenhardt, Stephan Seifert, Silke Szymczak Briefings in Bioinformatics 20, 492-503 (2019).