Closed rezacsedu closed 4 years ago
nothing stopping you! Although cancer-type (i.e. tissue type) is an easy signal to find
Thanks a million for the quick reply. Sorry, but I've one more stupid question, RE: issue#102 (https://github.com/greenelab/pancancer/issues/102):
Can the same labels (i.e., ttps://github.com/greenelab/pancancer/blob/master/data/sample_freeze.tsv ) be used (let's say) to create a shared representation of the features (out of 3 datasets) to train a multimodal network?
Yep! So the idea is that you'd train a model to detect something (say cancer-type) but the real endpoint you care about is how the multimodal network combines features together? (and then interpret the combinations?)
you care about is how the multimodal network combines features together? Yes, exactly.
Although with such a strong signal like cancer type, I worry that the models will be lazy and won't try to integrate too much
Can I combine gene expression, mutation, and copy number data for cancer types prediction?