Abstract Deciphering the highly coupled regulatory circuits that drive cellular dynamics remains a fundamental goal in biology. However, capturing the multi-scale time-lagged dynamics and combinatorial regulatory logic of gene regulation remains challenging. Here we present scMagnify, a deep-learning-based framework that leverages chromatin accessibility and gene expression via Granger causality to reconstruct and decompose multi-scale gene regulatory networks (GRNs).
