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TANDEM  

A Two-Stage Approach to Maximize Interpretability of Drug Response Models Based on Multiple Molecular Data Types
View on CRAN: Click here


Download and install TANDEM package within the R console
Install from CRAN:
install.packages("TANDEM")

Install from Github:
library("remotes")
install_github("cran/TANDEM")

Install by package version:
library("remotes")
install_version("TANDEM", "1.0.3")



Attach the package and use:
library("TANDEM")
Maintained by
Nanne Aben
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-06-08
Latest Update: 2019-11-25
Description:
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.
How to cite:
Nanne Aben (2016). TANDEM: A Two-Stage Approach to Maximize Interpretability of Drug Response Models Based on Multiple Molecular Data Types. R package version 1.0.3, https://cran.r-project.org/web/packages/TANDEM
Previous versions and publish date:
0.9.1 (2016-06-08 11:46), 0.9.2 (2016-07-11 19:01), 0.9.3 (2016-07-13 10:24), 1.0.0 (2016-09-20 00:59), 1.0.1 (2017-04-07 14:33), 1.0.2 (2017-06-15 15:40)
Other packages that cited TANDEM R package
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Other R packages that TANDEM depends, imports, suggests or enhances
Functions, R codes and Examples using the TANDEM R package
Some associated functions: coef.tandem . example_data . nested.cv . predict.tandem . relative.contributions . tandem . 
Some associated R codes: data.R . functions.R .  Full TANDEM package functions and examples
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