Additional file 11 of Correction for both common and rare cell types in blood is important to identify genes that correlate with age
Creators: name: Pellegrino-Coppola, Damiano
name: Claringbould, Annique
name: Stutvoet, Maartje
name: Dorret I. Boomsma
name: M. Arfan Ikram
name: P. Eline Slagboom
name: Harm-Jan Westra
name: Franke, Lude
Publisher: name: figshare
Year: 2021
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: FOS: Biological sciences

description: Additional file 11: Figure S1A. Heatmap of extended model predictors. A heatmap of Spearman correlations between all cell type predictors used in the extended model (EM). Figure S1B. Correlations of selected variable counts with age. The Spearman correlations of selected variables - including measured or imputed cell counts - with age are presented, colored per cohort (see legend). See Results section for details. Figure S2. Correlation of Z-scores associated with IM and EM genes. A Pearson correlation of the Z-scores associated with both significant and not significant IM and EM genes is shown. The 45° diagonal is presented as dashed, the correlation line is in red. See Results section for details. Figure S3. Cohort-related, gene-specific ρ values. A) QQ plots used to evaluate the distribution pattern of cohort-related, gene-specific ρ values. B) Gene expression residuals decrease with the EM. Homoscedasticity was evaluated by correlating gene expression residuals from every model with age, and the absolute Spearman ⍴ values obtained after meta-analysis are reported for all genes minus the shared genes significantly associated with aging. See Figure 2 in the main text and Methods for details. Statistical significance was assessed with a paired, one-tailed Wilcoxon test. The stars indicate statistical significance: *** P ≤ 0.001, ** P ≤ 0.01, * P ≤ 0.05. LL, LifeLines DEEP; LLS, Leiden Longevity Study; NTR, Netherlands Twin Registry; RS, Rotterdam Study; EM, extended model; IM, initial model; IM no age, IM without age as covariate; EM no age, EM without age as covariate. Figure S4. scRNA-seq data-derived t-SNE plots reveal that IM-related aging genes are more likely cell type-specific marker genes. Mean expression levels of cell type marker genes among aging-related genes identified in the Initial Model (IM, left) and in the Extended Model (EM, right) are plotted. Where applicable, IM- and EM-related intensities for same cell types plots were compared through a Wilcoxon test, always observing a P ≤ 2.2⨯10−16. For details regarding cell population-specific regions, refer to [20]. Figure S5. Heatmap of gene expression residuals correlations for EM downregulated aging-related genes. Downregulated EM aging-related genes were clustered based on the correlations of gene expression residuals and highly correlating clusters were identified and highlighted with a yellow border. See Results section for details. Figure S6. Expression values of platelet-related genes across age. The four cohorts are colored separately and the Spearman correlations and P-values are calculated for each cohort independently. Figure S7. Correlations between (residual) gene expression levels of the genes from platelet-related cluster 1 and measured platelet levels. A) Spearman correlations between gene expression levels and measured platelets, B) Spearman correlations between gene expression residuals from the extended model and measured platelets. Figure S8. scRNA-seq data-derived t-SNE plots reveal that PF4 and PPBP are specifically expressed in megakaryocytes. Mean expression levels of platelet marker genes PF4 and PPBP are plotted. For details regarding cell population-specific regions, refer to [20].