Comprehensive PanCancer Gene Signature Assessment Through the Implementation of a Cascade Machine Learning System
Repository to store the Pancancer code and data to replicate the study. The research presents an approach for pancancer diagnosis based on gene expression analysis that determines a reduced set of 12 genes, which makes it possible to distinguish between the main 14 cancer diseases by their current impact rate. The designed pipeline to achieve our goal can be seen below:
This research has been developed by using our R-Bioc Package KnowSeq. If you would like to use the package, please add the following citation to your document or research:
Castillo-Secilla, D., Gálvez, J. M., Carrillo-Perez, F., Verona-Almeida, M., Redondo-Sánchez, D., Ortuno, F. M., ... & Rojas, I. (2021). KnowSeq R-Bioc Package: The Automatic Smart Gene Expression Tool For Retrieving Relevant Biological Knowledge. Computers in Biology and Medicine, 104387.
To contact with the main author of this study for any doubt or consideration, please use the following e-mail: cased@ugr.es