dipm: an R package implementing the Depth Importance in Precision Medicine (DIPM) tree and Forest-based method

Summary The Depth Importance in Precision Medicine (DIPM) method is a classification tree designed for the identification of subgroups relevant to the precision medicine setting. In this setting, a relevant subgroup is a subgroup in which subjects perform either especially well or poorly with a part...

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Published inBioinformatics advances Vol. 2; no. 1; p. vbac041
Main Authors Chen, Victoria, Li, Cai, Zhang, Heping
Format Journal Article
LanguageEnglish
Published England Oxford University Press 2022
Subjects
Application Note
Bioinformatics
Precision medicine
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Summary:Summary The Depth Importance in Precision Medicine (DIPM) method is a classification tree designed for the identification of subgroups relevant to the precision medicine setting. In this setting, a relevant subgroup is a subgroup in which subjects perform either especially well or poorly with a particular treatment assignment. Herein, we introduce, dipm, a novel R package that implements the DIPM method using R code that calls a program in C. Availability and implementation dipm is available under a GPL-3 licence on CRAN https://cran.r-project.org/web/packages/dipm/index.html and at https://ysph.yale.edu/c2s2/software/dipm. It is continuously being developed at https://github.com/chenvict/dipm. Supplementary information Supplementary data are available at Bioinformatics Advances online.
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Victoria Chen and Cai Li wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.
ISSN:2635-0041
2635-0041
DOI:10.1093/bioadv/vbac041