Gene expression is a fundamental process whereby genetic information is expressed to control cellular identity and plasticity. Remarkably, in isogenic cell populations heterogeneity in gene expression is often found. This phenomenon is thought to be of importance for cell survival. In the context of cancer, these fluctuations may lead to the appearance of rare cells in the population capable to survive treatment. Since the emergence of drug resistance is a major challenge in disease treatment it is important to understand how heterogeneous gene expression occurs and is regulated in at a single cell level. Transcription is driven by transcription factors (TFs), which in turn recruit cofactors (CoFs), thereby modulating gene expression. However, currently it is not possible to study the effect of the various possible TF/CoFs pairs in single cells directly. This project will contribute to solve this problem and aims to develop a method that can simultaneously quantify (unknown) co-occurring TF/CoF pairs and the transcriptome at single cell resolution. Linking TFs/CoFs interactions with the phenotypic appearance of the cell may provide new insights in the regulation of gene expression in eukaryotes. Moreover, our approach may reveal interactions that only arise in a subset of the cell population, that remain hidden in bulk studies. Our method can be applied to any other set of protein-protein interactions, opening avenues for future research.