Fig. 4.

Comparative analysis of single cell metaVIPER performance compared to gene expression based methods. We identified the 100 most differentially expressed genes and differentially active proteins based on the analysis of five synthetic bulk samples created by averaging the expression of 100 randomly selected single cells from the melanoma, B cell, and T cell population clusters, respectively. a, b Based on t-SNE analysis, synthetic bulk samples clustered more tightly when analyzed based on VIPER-inferred protein activity than based on gene expression. c This panel shows the percent of the top 100 most differentially expressed genes/active proteins recapitulated as significantly differentially expressed/active in a given fraction of individual cells against the average expression/activity in a distinct cluster (e.g., a T cell vs. the average of all B cells). The yellow and turquoise curves (1-ECDF) and boxplots (median, lower/upper whiskers, and hinges) summarized the results of RSEM and metaVIPER-based analyses, respectively. d The same analyses were repeated to assess reproducible differential expression/activity of a gene/protein pair, as relevant for virtual FACS analyses. e, f Virtual FACS analyses using expression and activity of established lineage marker TFs by RSEM and metaVIPER-based analysis (see main text and Fig. 3 for details). g, h Virtual FACS analysis using expression and activity of STAT4 and POU2F—both identified as differentially expressed and active candidate biomarkers from bulk sample analyses—using the same methods. i, j Virtual FACS analysis based on expression and activity of CD3 and CD19 cell surface markers, as used in standard FACS analyses, using the same methods