Recent progress in single-cell technologies has enabled the identification of all major cell types in mouse. However, for most cell types, the regulatory mechanism underlying their identity remains poorly understood. By computational analysis of the recently published mouse cell atlas data, we have identified 202 regulons whose activities are highly variable across different cell types, and more importantly, predicted a small set of essential regulators for each major cell type in mouse. Systematic validation by automated literature and data mining provides strong additional support for our predictions. Thus, these predictions serve as a valuable resource that would be useful for the broad biological community. Finally, we have built a user-friendly, interactive web portal to enable users to navigate this mouse cell network atlas.
Keywords: cell type; co-expression analysis; database; gene regulatory network; mouse cell atlas; single-cell RNA-seq; text mining; transcription factor; visualization; web application.
Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.