Abstract 2452 BITFAM 2.0: Decoding Transcription Factor Activity with an Improved Bayesian Model to Identify Cell Type-Specific Regulators of Gene Expression

Transcription factors (TFs) are pivotal regulators of gene expression, orchestrating cellular processes, development, and disease progression. Studying TF activity at the cellular level offers profound mechanistic insights into these biological processes. We developed a biologically informed Bayesian inference transcription factor activity model (BITFAM), designed to predict the TF activity in individual cells by decomposing observed log-transformed, normalized transcriptional profiles into the product of TF activity and associated regulatory weights.