Research Paper Volume 15, Issue 24 pp 15451—15472
Identification and validation of key biomarkers associated with macrophages in nonalcoholic fatty liver disease based on hdWGCNA and machine learning
Figure 4. Pseudo-Time trajectory and SCENIC analysis. (A) pseudo-time distribution of the different macrophage subtypes. (B) Heatmap showing the change of potential feature genes in pseudo-time developmental trajectories. (C) Heatmap of RAS activity of transcription factors (TFs) in each sample, with negative correlations in blue and positive correlations in red. (D) Heatmap of the area under the curve (AUC) scores of TFs in each group. (E, F) Ranking of TFs in NASH and normal samples calculated by the RSS specificity score. (G) The correlation between SCENIC-identified TFs and 30 potential feature genes.