biospear

Biomarker selection in penalized regression models

Aim

We proposed biospear, a useful R tool for developing and validating prediction models, estimate expected survival of patients and visualize them graphically. A function generating simulated survival data set is also provided.

Install directly from github

#Could be needed to install some of these packages first

#install.packages(c("cobs", "grplasso", "mboost", "plsRcox", "pROC", "PRROC", "RCurl", "survAUC"))

#install.packages(c("dplyr", "glmnet", "corpcor", "survival","statnet.common","devtools"))

install.packages("BiocManager")

BiocManager::install(c("survcomp"))

library(devtools)

install_github("oncostat/biospear",type="source")

References

Ternès N, Rotolo F, Michiels S. biospear: an R package for biomarker selection in penalized Cox regression. Bioinformatics 2018 Jan 1;34(1):112-113. DOI: 10.1093/bioinformatics/btx560.

Ternes N, Rotolo F and Michiels S. Empirical extensions of the lasso penalty to reduce the false discovery rate in high-dimensional Cox regression models. Statistics in Medicine 2016;35(15):2561-2573. DOI: 10.1002/sim.6927

Ternes N, Rotolo F, Heinze G and Michiels S. Identification of biomarker-by-treatment interactions in randomized clinical trials with survival outcomes and high-dimensional spaces. Biometrical journal 2017 59(4):685-701. DOI: 10.1002/bimj.201500234

Ternes N, Rotolo F and Michiels S. Robust estimation of the expected survival probabilities from high-dimensional Cox models with biomarker-by-treatment interactions in randomized clinical trials. BMC Medical Research Methodology. 2017 17:83. DOI: 10.1002/bimj.201500234