Complete codes (Rmd notebook file) and data to test the DORGE machine-learning model used in the DORGE paper can be found in DORGE_tool_reproduce.zip. For your convenience, illustrative codes of the DORGE machine-learning model used in the DORGE paper can be found at https://biocq.github.io/DORGE/DORGE.html. An online video that explains the code is available at https://www.youtube.com/watch?v=Pk8ZqoHK8zk.
Codes to visualize the prediction by Shiny app can be found at the DORGE_shiny folder in the website indicated above.
The auxiliary datasets that are necessary to process raw data were hosted at Figshare https://figshare.com/projects/DORGE_Discovery_of_Oncogenes_and_Tumor_SuppressoR_Genes_Using_Genetic_and_Epigenetic_Features/78249, please note they are extreme large.
Further details are available at https://github.com/biocq/DORGE_codes.
Copyright: Content may be subjected to copyright.
How to cite:
Readers should cite both the Bio-protocol preprint and the original research article where this protocol was used:
Lyu, J, Li, J and Li, W(2022). Datasets used in this study. Bio-protocol Preprint. bio-protocol.org/prep1683.
Lyu, J., Li, J. J., Su, J., Peng, F., Chen, Y. E., Ge, X. and Li, W.(2020). DORGE: Discovery of Oncogenes and tumoR suppressor genes using Genetic and Epigenetic features. Science Advances 6(46). DOI: 10.1126/sciadv.aba6784
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