|Title||Detection Of Cooperatively Bound Transcription Factor Pairs Using ChIP-seq Peak Intensities And Expectation Maximization|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Datta V, Siddharthan R, Krishna S|
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-qeq 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. This suggests that peak intensities contain information that can help detect the cooperative binding of a TF pair. The incorporation of peak intensities into existing sequence-based methods would allow them to detect new sequences capable of being cooperatively bound by TFs. The CPI-EM algorithm is available at https://github.com/vishakad/cpi-em.