Deep learning models have achieved state-of-the-art performance at predicting diverse genomic modalities, yet their promise for biological discovery lies in how they are used after demonstrating their predictive performance. Here, we describe the functionality of tangermeme, a highly optimized toolkit for "everything-but-the-model" when it comes to genomic deep learning, and demonstrate how tangermeme can be used to distill the learned cis-regulatory patterns from models into human-interpretable insights.
Jacob Schreiber (Tue,) studied this question.