iRF specifications


Unique identifier OMICS_24054
Name iRF
Alternative name iterative Random Forest
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 2.0
Computer skills Advanced
Version 2.0.0
Stability Stable
methods, RColorBrewer, Matrix, Rcpp, dplyr, data.table, MASS, foreach, doParallel, rgl, R(≥3.1.2), AUC
Source code URL
Maintained Yes




No version available



  • person_outline Karl Kumbier
  • person_outline Bin Yu
  • person_outline Sumanta Basu
  • person_outline James Brown

Publication for iterative Random Forest

iRF institution(s)
Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, USA; Statistics Department, University of California, Berkeley, CA, USA; Centre for Computational Biology, School of Biosciences, University of Birmingham, Birmingham, UK; Molecular Ecosystems Biology Department, Lawrence Berkeley National Laboratory, Berkeley, CA, USA; Preminon, LLC, Las Vegas, NV, USA; Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
iRF funding source(s)
Supported by grants NHGRI U01HG007031, ARO W911NF1710005, ONR N00014- 16-1-2664, DOE DE-AC02-05CH11231, NHGRI R00 HG006698, DOE (SBIR/STTR) Award DE-SC0017069, DOE DE-AC02-05CH11231, NSF DMS-1613002, the Center for Science of Information (CSoI), a US NSF Science and Technology Center, under grant agreement CCF-0939370 and the National Library Of Medicine of the NIH under Award Number T32LM012417.

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