TANDEM: A Two-Stage Approach to Maximize Interpretability of Drug Response Models Based on Multiple Molecular Data Types

A two-stage regression method that can be used when various input data types are correlated, for example gene expression and methylation in drug response prediction. In the first stage it uses the upstream features (such as methylation) to predict the response variable (such as drug response), and in the second stage it uses the downstream features (such as gene expression) to predict the residuals of the first stage. In our manuscript (Aben et al., 2016, <doi:10.1093/bioinformatics/btw449>), we show that using TANDEM prevents the model from being dominated by gene expression and that the features selected by TANDEM are more interpretable.

Install the latest version of this package by entering the following in R:
install.packages("TANDEM")
AuthorNanne Aben
Date of publication2017-04-07 12:33:36 UTC
MaintainerNanne Aben <nanne.aben@gmail.com>
LicenseGPL-2
Version1.0.1

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Files

inst
inst/doc
inst/doc/my-vignette.html
inst/doc/my-vignette.Rmd
inst/doc/my-vignette.R
NAMESPACE
NEWS.md
data
data/example_data.rda
R
R/data.R R/functions.R
vignettes
vignettes/my-vignette.Rmd
README.md
MD5
build
build/vignette.rds
DESCRIPTION
man
man/tandem.Rd man/relative.contributions.Rd man/predict.tandem.Rd man/nested.cv.Rd man/coef.tandem.Rd man/example_data.Rd

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