WTKO-CNN: Deep Learning Reveals Sequence Motifs Distinguishing Wild-Type and Knockout ATAC-seq Peaks
WTKO-CNN is a novel two-layer neural network that classifies DNA sequences as Wild-Type or Knockout based on ATAC-seq data. It uses attention mechanisms and saliency maps to interpret its decisions, allowing researchers to discover specific sequence motifs that distinguish WT from KO chromatin accessibility regions, providing mechanistic insight into gene knockout effects.