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COSMONET: A R package for survival analysis using screening-network methods
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README.md

README.md

COSMONET

We propose new multistage computational-statistical strategies based on screening-network methods that predict patient survival outcome by screening key survival-related genes [1,2]. In particular, we use: (i) screening approaches to reduce the initial dimension from an high-dimensional space p to a moderate scale d; (ii) Cox-regression model for describing the relationship between patient survival times and predictor variables; (iii) network-penalized Cox-regression approaches to model observed survival time through genome-wide omic profiles while accounting for coordinated functioning of genes in the form of biological pathways or networks.

References

[1] Iuliano et al. (2018). Combining pathway identification and breast cancer survival prediction via screening-network methods. Frontiers in genetics, 9.

[2] Iuliano et al. (2016). Cancer markers selection using network-based Cox regression: A methodological and computational practice. Frontiers in physiology, 7, 208.

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