GRNsmile: gene regulatory network inference with a single-cell multi-layer omics approach [scRNA-seq]

scRNA-seq and 10X scATAC-seq performed on mixed hESC-dreived cardiomyocyte on day 0, 2, 4, 6, 8 and 15. And MicroC performed on hESC-dreived cardiomyocyte on day 0 and 15. Overall design: We present an integrated framework GRN-smile to infer gene regulatory networks from multiple layers of regulatory information. We tested this framework with a well-studied biological process: differentiation of hESC to cardiomyocyte. Cells were collected and mixed to mimic a complex tissue sample during in vitro cardiac differentiation of human ESCs(day 0, 2, 4, 6, 8 and 15). This artificial sample was profiled by 10X scRNA-seq and 10X scATAC-seq. And MicroC performed on hESC-dreived cardiomyocyte on day 0 and 15. To detect long-range cis-linkages, we generated 4 replicates of Micro-C in day 0 hESC-dreived cardiomyocyte and 2 replicates of Micro-C in day 15 hESC-dreived cardiomyocyte.