CNAttention: an attention-based deep multiple-instance method for uncovering CNA signatures across cancers
This tool aims to uncovering copy number abbresion (CNA) patterns of pan-cancer based on large CNA data from progenetix database.
Firstly you have to make sure that you have all dependencies in place. The simplest way to do so, is to use anaconda.
You can create an anaconda environment called cnattention.
conda env create -f requirements.txt
conda activate cnattention
python CNAttention.py
The script CNAttention.py takes the CNA profiles as input and output the attention parameters for all CNA features, accuracy of bag and instance classification. The users can adjust the number of selected features as the final pattern of different cancers.
The users can visualize the selected CNA patterns on progenetix database by simply type in the feature gene names of a specific cancer type.
