%0 Journal Article %A Vishaka Datta %A Rahul Siddharthan %A Sandeep Krishna %T Detection of cooperatively bound transcription factor pairs using ChIP-seq peak intensities and expectation maximization %D 2017 %R 10.1101/120113 %J bioRxiv %P 120113 %X 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 maximization (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. %U https://www.biorxiv.org/content/biorxiv/early/2017/04/10/120113.full.pdf