Allows the user to incorporate multiple sources of co-data
(e.g., previously obtained p-values, published gene lists, and annotation) in the estimation of a logistic regression model to enhance predictive performance and feature selection, as described in Münch, Peeters, van der Vaart, and van de Wiel (2018)
If you encounter any problems while using the package, or if you have any suggestions for additions/improvements, please don't hesitate to contact the author.
NOTE: the VIGNETTE is included in the package and contains two mehtylation data examples.
Münch, M.M., Peeters, C.F.W., van der Vaart, A.W., and van de Wiel, M.A. (2018). Adaptive group-regularized logistic elastic net regression. arXiv:1805.00389v1 [stat.ME].
This is the first version, so no changes are available