Integrative Subtype Generation
Clustering to find patient subtypes
Combine iSubGen integrative features
Write scaling factors to file
Apply scaling factors
Calculate consensus integrative correlation matrix
Calculate integrative similarity matrix
Calculate scaling factors
Create matrix of independent reduced features
Create an autoencoder for dimensionality reduction
Load molecular aberration data
Read scaling factors from file
Multi-data type subtyping, which is data type agnostic and accepts missing data. Subtyping is performed using intermediary assessments created with autoencoders and similarity calculations. See Fox et al. (2024) <doi:10.1016/j.crmeth.2024.100884> for details.
Useful links