Extended Data Fig. 5: Validation of hematopoetic TF regulons in human datasets and TFA patterns of macrophage-specific TFs in lung adenocarcinoma.
From: Inference of age-associated transcription factor regulatory activity changes in single cells
a-b) Validation of hematopoetic TF regulons in human datasets. a) Barplots displaying the validation accuracy of blood cell-type specific SCIRA TF-regulons in 3 independent human FACS mRNA expression datasets (Ebert, Schultze & de Graf) from the Haemopedia resource. Accuracy was estimated as the fraction of cell-type specific TFs whose regulons predicted a significantly higher TFA in the corresponding blood cell types compared to all other cell-types, as assessed using a one-sided t-test (P < 0.05). Only cell-types with at least 5 samples were included in this analysis. Total number of cell-sorted samples per dataset were: n = 211 (Ebert), n = 384 (Schultze), n = 42 (de Graf). b) Left panel: tSNE-diagram of a 10X scRNA-Seq peripheral blood mononuclear cell (PBMCs) dataset from Zheng et al. Right panel: Barplot displaying the validation accuracy of blood cell type specific TF-regulons derived from cell-sorted bulk expression data from Haemopedia in the scRNA-Seq PBMC data from Zheng et al. c-e) Pattern of TFA of macrophage-specific TFs in lung adenocarcinoma TCGA set. c) Color bars displaying the t-statistics (t) and P-values (P) between the TFA of 11 macrophage-specific TFs and normal-cancer status using only paired samples (n = 45 pairs). Thus, cyan indicates lower TFA in tumor vs normal. d) As a), but now adjusted for macrophage marker (LYZ & CD14) expression. e) Kaplan Meier overall survival curves for all primary LUAD samples, with samples stratified into low, middle and high tertiles according to IRF2 TFA activity. Hazard Ratio and chi-square test P-value derive from a Cox-regression of IRF2 TFA (treated as continuous variable).
