How to Classify Lung Cancer Subtype from DNA Copy Numbers Using PyTorch

A convolutional neural network can be built using PyTorch to classify lung cancer subtypes based on DNA copy number (CN) profiles. These CN profiles represent large-scale genomic changes, such as the addition or removal of millions of DNA bases, which are often specific to cancer types. The process involves using a tool called CNSistent to preprocess raw genomic data, which has non-uniform segment lengths, into fixed-size bins suitable for a neural network input. The guide focuses on differentiating between lung adenocarcinoma (LUAD) and squamous-cell carcinoma (LUSC), providing code for data preparation and defining the CNN model.