netDx is a patient classifier algorithm that can integrate several types of patient data into a single model. It does this by converting each type of data into a view of patient similarity; i.e. by converting the data into a graph in which more similar patients are tightly linked, while less similar patients are not so tightly linked.
Go here to see vignettes (worked examples) and install software.
Methods paper:Pai S, Hui S, Isserlin R, Shah MA, Kaka H, GD Bader (2019)
netDx: interpretable patient classification using integrated patient similarity networks.
Molecular Systems Biology 15, e8497
Software update:Pai S, Weber P, Isserlin R, Kaka H, Hui S, Shah MA, Giudice L, Giugno R, Nøhr AK, Baumbach J, GD Bader
netDx: Software for building interpretable patient classifiers by multi-'omic data integration using patient similarity networks
**netDx is under active development to make the workflow easier to use. The vignettes on the BioConductor page (above) are the latest source of information.
Contact Shraddha Pai, firstname.lastname@example.org
This page last updated 22 Sep 2021.