Abstract
Transcription factors (TFs) often work cooperatively, where the binding of one TF to DNA enhances the binding affinity of a second TF to a nearby location. Such cooperative binding is important for activating gene expression from promoters and enhancers in both prokaryotic and eukaryotic cells. Existing methods to detect cooperative binding of a TF pair rely on analyzing the sequence that is bound. We propose a method that uses, instead, only ChIP-Seq peak intensities and an expectation maximisation (CPI-EM) algorithm. We validate our method using ChIP-seq data from cells where one of a pair of TFs under consideration has been genetically knocked out. Our algorithm relies on our observation that cooperative TF-TF binding is correlated with weak binding of one of the TFs, which we demonstrate in a variety of cell types, including E. coli, S. cerevisiae, M. musculus, as well as human cancer and stem cell lines. We show that this method performs significantly better than a predictor based only on the ChIP-seq peak distance of the TFs under consideration. By explicitly avoiding the use of sequence information, our method may help uncover new sequence patterns of cooperative binding that sequence based methods could build upon. The CPI-EM algorithm is available at https://github.com/vishakad/cpi-em.
