A. Heatmap of cell viability in regulon subsets. B. Network of the regulation of expression by TFs and target genes. The top 100 genes were selected for the screen.[1]
Heatmap showing the activated TFs predicated by SCENIC. For each cell type, the top 10 -log(P value) specific TFs being activated are shown, which ranked by number of cells. Columns are individual cells and rows are individual genes. White: not activated; red: activated. [2]
Prediction of activated TFs
The modules of TFs were identified by the SCENIC python workflow (version 0.9.1) using default parameters(https://scenic.aertslab.org/). A human TF gene list was collected from the resources of pySCENIC(https://github.com/aertslab/pySCENIC/tree/master/resources), animal TFDB(http://bioinfo.life.hust.edu.cn/HumanTFDB#!/download)and the Human Transcription Factors database(http://humantfs.ccbr.utoronto.ca/download.php). Activated TFs were identified in the AUC matrix, and differentially activated TFs were selected using FindAllMarkers of the Seurat package. The top 10 enriched activated TFs were ranked by -log10(p_value) and
demonstrated using the binary matrix (1 activated; 0 not activated). Networks of the modules with TFs and their target genes were visualized by the R package igraph.