Benchmarking tools for transcription factor prioritization

• DOI: 10.1016/j.csbj.2024.05.016
• Publication Date: 2024-05-11T15:50:58Z
• Authors: Leonor Schubert S...; Alejandro Reyes; Sebastian Hoersch; Enrico Ferrero; Christian Kolter; Swann Gaulis; Sebastian Steinha...
• Keywords: DNA binding site; Epigenomics; Epigenome; Benchmarking; Profiling (computer programming)

Spatiotemporal regulation of gene expression is controlled by transcription factor (TF) binding to regulatory elements, resulting in a plethora cell types and states from the same genetic information. Due importance various sequencing methods have been developed localise them genomes, for example using ChIP-seq profiling histone mark H3K27ac that marks active regions. Moreover, multiple tools predict TF these elements based on DNA sequence. As altered hallmark disease phenotypes, identifying TFs driving such programs critical identification novel drug targets. In this study, we curated 84 chromatin experiments (H3K27ac ChIP-seq) where were perturbed through e.g., knockout or overexpression. We ran nine published prioritize real-world datasets evaluated performance TFs. This allowed nomination three frontrunner tools, namely RcisTarget, MEIRLOP monaLisa. Our analyses revealed opportunities commonalities will help guide further improvements developments field.