Fig. 1: Curation of human cytokine-response data.
From: Systematic investigation of cytokine signaling activity at the tissue and single-cell levels
a, The FDC can automatically process RNA-seq and MicroArray transcriptomic data from public repositories. Then, with the FDC’s natural language processing functions, curators read the metadata of each sample to annotate experimental conditions, including cytokine treatment, cell model, dose and duration. The output is differential logFC upon treatment. b, Two uses of the CytoSig framework: (1) query a gene name to view upstream cytokine regulators or downstream target genes (if the query is a cytokine); (2) predict cytokine signaling activities through transcriptomic profiles using a linear regression model. Input, the input transcriptomic profile of the sample as the response variable in regression; signature, the average response signature of cytokines as explanatory covariates; activity, the regression coefficients reflecting signaling activities. c, Count of treatment response profiles with biological replicates for different molecule types. d, Example correlation between the expression of IL-10 target genes and its ligand or receptor. Each dot represents a TCGA lung adenocarcinoma sample (n = 513). The x axis shows the expression of IL10 or receptor (IL-10RA + IL-10RB). The y axis presents the expression scores of IL-10 targets from a monocyte treatment experiment. Pearson correlation (r) indicates the human physiological relevance of the current data. e, Distribution of target score correlations. Correlations were computed using all cytokine-response profiles and TCGA or GTEx expression matrices. Distributions of correlations are shown by violin plots, smoothed by a kernel density estimator, for both real and randomized data through gene label permutations. The P value, calculated with the one-sided Wilcoxon signed-rank test, represents the statistical significance of correlations being higher than zero (n = 112 ligands and n = 111 receptors). f, Similarity of signaling response profiles. We created a composite signature for each cytokine that consisted of the median logFC across all experiments and then calculated pairwise correlations between composite signatures for the hierarchical clustering. Red branches highlight the clusters of similar cytokines discussed in the paper.
