Protocol for obtaining cancer type and subtype predictions using subSCOPE - Jasleen K. Grewal; A. Gordon Robertson; Kyle Ellrott; Christopher K. Wong; Jordan A. Lee; Christina Yau; Bahar Tercan; Mauro A.A. Castro; Christopher C. Benz; Jean C. Zenklusen; Andrew D. Cherniack; Peter W. Laird; et al. (STAR Protocols)
Summary: We present a protocol for obtaining cancer type and subtype predictions using a machine learning method (subSCOPE). We describe steps for data preparation, subSCOPE setup, and running subSCOPE inference on prepared data. The protocol supports five -omics data types as input (DNA methylation, gene expression, microRNA [miRNA] expression, point mutations, and copy-number variants) and allows individual cancer type and data type selection. For non-The Cancer Genome Atlas (TCGA) cancer samples, it provides subtype-level classification across 26 different TCGA cancer cohorts and 106 subtypes.For complete details on the use and execution of this protocol, please refer to Ellrott et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.