netReg fits linear regression models using network-regularization. Network-regularization used graph prior as penality for the coefficients of linear models. The graph can represent any relationship between the covariables/responses of the model, for instance, some quantifiable biological relationship such as coexpression.
netReg uses Armadillo and TensorFlow for fast matrix computations and optimization.
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Fabian J (2018),
netReg: Network-regularized linear models for biological association
studies.
Bioinformatics
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Tensorflow: A system for large-scale machine learning.
12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16)
Powell M.J.D. (2009),
The BOBYQA algorithm for bound constrained optimization
without derivatives.
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Eddelbuettel, Dirk and Sanderson, Conrad (2014),
RcppArmadillo: Accelerating R with high-performance C++ linear algebra.
Computational Statistics & Data Analysis